{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 199,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import scipy.signal as signal\n",
    "import scipy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "metadata": {},
   "outputs": [],
   "source": [
    "def realignment_coeffs(data):\n",
    "    \"\"\"\n",
    "    对系数进行隔列插零\n",
    "    \"\"\"\n",
    "    z = np.zeros(data.shape[0])\n",
    "    for i in range(data.shape[1]-1,0,-1):\n",
    "        data = np.insert(data,i,z,axis=1)\n",
    "    return data\n",
    "\n",
    "def realignment_data(data,channel_num):\n",
    "    disp_len = int(np.ceil(data.size / channel_num))\n",
    "    patch_size = int(disp_len * channel_num - data.size)\n",
    "    patch_data = np.concatenate((data, np.zeros(patch_size)))\n",
    "    polyphase_data = np.zeros(patch_data.size*2) \n",
    "    half = (channel_num // 2)\n",
    "    for i in range(patch_data.size // half):\n",
    "        if(i == (patch_data.size // half - 1)):\n",
    "            polyphase_data[i*channel_num+half:(i+1)*channel_num] = patch_data[i*half:(i+1)*half]\n",
    "        else:\n",
    "            polyphase_data[i*channel_num+half:(i+1)*channel_num+half] = list(patch_data[i*half:(i+1)*half])*2\n",
    "    polyphase_data = polyphase_data.reshape( (channel_num, -1), order='F')\n",
    "    polyphase_data = np.flip(polyphase_data,0)\n",
    "    return polyphase_data\n",
    "\n",
    "def gen_filter_coeffs(numtaps, M):\n",
    "    coeffs = scipy.signal.firwin(numtaps*M, cutoff=2.0/M, window=\"hamming\")\n",
    "    coeffs = np.reshape(coeffs, (M, -1), order='F')\n",
    "    coeffs = realignment_coeffs(coeffs)\n",
    "    return coeffs\n",
    "\n",
    "def my_coeffs(coeffs, M):\n",
    "    coeffs = np.reshape(coeffs, (M, -1), order='F')\n",
    "    coeffs = realignment_coeffs(coeffs)\n",
    "    return coeffs\n",
    "\n",
    "def polyphase_filter(data,filter_coeffs,channel_num):   \n",
    "     \n",
    "    polyphase_data = realignment_data(data, channel_num)\n",
    "    polyphase_data = polyphase_data.reshape( (channel_num, -1), order='F')\n",
    "    \n",
    "    # print(polyphase_data)\n",
    "    \n",
    "    filt_data = np.zeros(polyphase_data.shape)\n",
    "    for k in range(channel_num):\n",
    "        filt_data[k] = scipy.signal.lfilter(filter_coeffs[k], 1, polyphase_data[k])\n",
    "        # filt_data[k] = scipy.signal.rfilter(filter_coeffs[k], 1, filt_data[k])\n",
    "\n",
    "    dispatch_data = np.fft.fft(filt_data, axis=0)\n",
    "    return dispatch_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "metadata": {},
   "outputs": [],
   "source": [
    "def apply_chirp(freq,size,bw=400.0,fc=1382.0):\n",
    "    dm = 2.64476\n",
    "    dm_dispersion = 2.41e-4\n",
    "    dispersion_per_MHz = 1e6 * dm / dm_dispersion\n",
    "    phasors = np.zeros((size),dtype=complex)\n",
    "    binwidth = -bw / size\n",
    "    coeff = 2 * np.pi * dispersion_per_MHz / (fc * fc);\n",
    "    for i in range (size):\n",
    "        f = i * binwidth + 0.5 * bw\n",
    "        phasors[i] = np.exp(1j * coeff * f * f / (fc+f));\n",
    "        if i == 0:\n",
    "            phasors[i] = 0; \n",
    "        freq[i] = phasors[i] * freq[i];\n",
    "\n",
    "def get_period_size(bw):\n",
    "    period = 0.00575730363767324\n",
    "    return int(period * bw * 1e6)\n",
    "\n",
    "def fold_data(data,blocks,psize):\n",
    "    cur = 0\n",
    "    pdata = np.zeros((psize))\n",
    "    pnum = np.zeros((psize))\n",
    "    for i in range(blocks):\n",
    "        if(cur >= psize):\n",
    "            cur = 0\n",
    "        pnum[cur] = pnum[cur] + 1\n",
    "        pdata[cur] = (pnum[cur] - 1) * pdata[cur] / pnum[cur] + data[i] / pnum[cur]\n",
    "        cur = cur + 1 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {},
   "outputs": [],
   "source": [
    "def kernel(data,coeffs,nchannels):\n",
    "       # coeffs = gen_filter_coeffs(ntaps,channel_num)  \n",
    "    subfreq = polyphase_filter(data,coeffs,nchannels)\n",
    "    # subfreq = np.flip(subfreq,axis=0)\n",
    "    b = np.append(subfreq[0],np.flip(subfreq[1:],axis=0))\n",
    "    subfreq = b.reshape((nchannels,-1))\n",
    "    freq_size = subfreq.shape[1]\n",
    "    N = int(freq_size * nchannels // 4)\n",
    "    myfreq = np.zeros((N), dtype=complex)\n",
    "    start = 0\n",
    "    end = 0\n",
    "    mystart = 0\n",
    "    myend = 0\n",
    "    bw = 0\n",
    "    for i in range(nchannels // 2 + 1):\n",
    "        mystart += bw\n",
    "        if i == 0:\n",
    "            start = freq_size // 2\n",
    "            end = freq_size // 2 + freq_size // 4\n",
    "        elif i == nchannels // 2:\n",
    "            start = freq_size // 2 - freq_size // 4\n",
    "            end = freq_size // 2 \n",
    "        else:\n",
    "            start = freq_size // 2 - freq_size // 4\n",
    "            end = freq_size // 2 + freq_size // 4\n",
    "        bw = end - start\n",
    "        myend = mystart + bw\n",
    "        \n",
    "        if i % 2 == 0:\n",
    "            myfreq[mystart:myend] = scipy.fft.fftshift(scipy.fft.fft(subfreq[i]))[start:end]\n",
    "        else:\n",
    "            myfreq[mystart:myend] = scipy.fft.fft(subfreq[i])[start:end]\n",
    "    # opfb_t = np.abs(scipy.fft.fft(myfreq))\n",
    "    \n",
    "    return myfreq,subfreq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "metadata": {},
   "outputs": [],
   "source": [
    "def integral_data(data,size,n=1024):\n",
    "    data = np.abs(data)\n",
    "    bins = size // n\n",
    "    out = np.zeros((1024))\n",
    "    sum = 0\n",
    "    index = 0\n",
    "    i = 0\n",
    "    while(1):\n",
    "        sum = 0\n",
    "        j = 0\n",
    "        while(1):\n",
    "            if j > bins or i > (bins * (n-1)):\n",
    "                break\n",
    "            sum += data[i]\n",
    "            i += 1\n",
    "            j += 1\n",
    "        out[index] = sum / j\n",
    "        index += 1\n",
    "        # print(i)\n",
    "        if i > (bins * (n-1)):\n",
    "            break\n",
    "    sum = 0\n",
    "    while(1):\n",
    "        if i >= size:\n",
    "            break\n",
    "        sum += data[i]\n",
    "        i += 1\n",
    "    \n",
    "    out[n-1] = sum / (size - n * bins + bins);\n",
    "    return out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "metadata": {},
   "outputs": [],
   "source": [
    "coeffs = np.loadtxt(\"coeffs.txt\")\n",
    "data = np.loadtxt(\"time_24.txt\")\n",
    "ocoeffs = my_coeffs(coeffs,16)\n",
    "fullfreq,myfreq = kernel(data,ocoeffs,16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "metadata": {},
   "outputs": [],
   "source": [
    "ifull = integral_data(fullfreq,fullfreq.shape[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1292cfac0>]"
      ]
     },
     "execution_count": 206,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "plt.plot(ifull)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x12a0e8040>]"
      ]
     },
     "execution_count": 207,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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j6NChOO+887By5UrjOadMmYIuXbqk/xs0aFAut0EIPtu4E996YA5Ou/st+Qvu/UgJEjdZhjgeSAki9vtGDgJCio6shaFkMokrr7wSEyZMwAEHHGA87txzz8UvfvELHHHEESgrK8Nee+2FY445Bj/72c/Sx4wfPx4PPfQQpk2bhnvuuQfLly/HkUceiR07dmjPee2112L79u3p/1atWpXtbRACAFi+sVb7OZc9UopEIwbLEEcEKUGStAwRUtRkHZgzadIkLFiwAG+++abvcTNmzMBtt92GP//5zxg/fjyWLl2KK664ArfccgtuuOEGAMCXv/zl9PEHHnggxo8fjz333BNPPvkkLr30Us85KyoqUFFRkW3TCbGGbnKkFInHMsKQmD2LSnFSish1hjgICCk2shKGJk+ejOeeew6vv/46Bg4c6HvsDTfcgAsuuACXXXYZAGDkyJGora3Ft7/9bVx33XWIRr3Gqa5du2L48OFYunRpNs0jJDSCIlyCshApRaQ6Q4wZIiWOFDNEjQAhRUcoNznHcTB58mQ8/fTTePXVVzFkyJDA3+zatcsj8MRisfT5dOzcuROfffYZ+vXrF6Z5hGSNURhq3WYQ0iYQU2uLcB9IShHWGSKkuAllGZo0aRIee+wxPPvss6iursa6desAAF26dEFVVRUA4MILL8SAAQMwZcoUAMCpp56KO++8EwcffHDaTe6GG27AqaeemhaKfvzjH+PUU0/FnnvuiTVr1uCmm25CLBbDOeeck897JSQ01ISTUiRm0A7QbZSUIlIChYQDx3EQMWnQCCHtjlDC0D333AMAOOaYY6TPH3zwQVx00UUAgJUrV0qWoOuvvx6RSATXX389Vq9ejV69euHUU0/FL3/5y/QxX3zxBc455xxs3rwZvXr1whFHHIFZs2ahV69eWd4WIfmBez9SipiEHo4HUoqo4yGRdKS4OkJI+yaUMGSjJZ8xY4Z8gXgcN910E2666Sbjb6ZOnRqmGYS0GsyeRUqRhGGup2WIlCJqt29KOojHCtMWQkj+yanOECHFQgR6LR/3fqQUSRqCgzgeSCmijgcmUSCkuKAwRIgPXPNIKULLECEZ1HWAtYYIKS4oDBHiAxMokFLElDCLw4GUIqoSoJG1hggpKigMEeIDlzxSipgsQLQMkVJEVYoxvTYhxQWFIUIAGEKGaBkiJUmCMUOEpPG6yXEgEFJMUBgixAdu/kgpQssQIRnUfs8ECoQUFxSGCPGBSx4pRUyWIQpDpBTxCENMoEBIUUFhiBAYveS4+SMlidFNrpXbQUhbQA0RYgIFQooLCkOEAIhEWGeIEBeTF5DjMI6OlB6qUoxKMkKKCwpDhPjAJY+UIibLEEAFASk91OHAMUBIcUFhiBAfqAUnpYip6CpArTgpPdR1wG98EELaHxSGCIFZ6OGaR0qRpI9liIm0SKlBNzlCihsKQ4TA7A7n0FGOlCB+mm+OCVJqeN3kOAYIKSYoDBEC8+LGQuOk1HAcx9ciyn0gKTW8lqECNYQQ0iJQGCIEZqGHax4pNfySJwB0ESKlh9rlg8YIIaR9QWGIEJg3eNz4kVIjaJ/HfSApNRgzREhxQ2GIEJgtQH6B5IQUI0EbPcZLkFJDHRMcAoQUFxSGCIF5g9dIYYiUGMFucq3UEELaCGqfp2WIkOKCwhAhMG/wmhLMoEBKi6AaKrQMkVLDU2eIGgFCigoKQ4TArOnjokdKjSDXUA4JUmp4U2sXph2EkJaBwhAhMC9ujQmueqS0YDY5QmSYQIGQ4obCECEwL250kyOlhusmF4nIn7v/5j6QlBqqfoAeA4QUFxSGCIGPZYiLHikx3JpbMUUaijb/mzFDpNRQ+zyXBUKKCwpDhICWIUJcXMtQNCoLQ+6/uBEkpYZqCaJCgJDigsIQIfDJJsedHykx3AQKJssQ4yVIqeGNGSpQQwghLQKFIULgU2eIliFSYrha8KghZojCECk1PDFDHAOEFBUUhgiBOWaoidnkSIlhcpPLxAy1epMIKSiqsoxucoQUFxSGCIFPzFCSliFSWrgbvZgaM8RscqREUS1DtI4SUlxQGCIEZh9w1hkipUYiIJscN4Kk1PDEDFFHRkhRQWGIEAAOmE2OEECIGTJYhigMkVKDMUOEFDcUhgiBj2WIaYNIieEKO8Y6Q63eIkIKi+s6Go3I/yaEFAcUhgiBeXGjZYiUGq5lSI0Z4kaQlCqugiAeizb/u5CtIYTkGwpDhCBTW0WF2eRIqZHJJid/HknHDLV2iwgpLG6MULxZI6AWYSWEtG8oDBECs+sP3eRIqWEuutr8PS1DpMRIKhkWaR0lpLigMEQIvNruslhq0aObHCk1zAkUmi1DHBKkxHBlnzK6yRFSlFAYIgReTV9FPAaAbnKktNiwoy6dTt5kGTJlXiSkWFEtQ7SOElJcxAvdAELaAuriVhGPYmc90Eg1OCkR5q/ciq/9+e30v91gcZd0NjnuA0mJkU6gwJghQooSWoYIgXeDVxFPDQ1ahkip8Oisz6V/x1U3ueb/UytOSg23y2dihgrYGEJI3qEwRAi8PuAVZSk3uUbGDJESIQJZ+FFTazObHClVXAVAJmaIg4CQYoLCECHwLm7lzYteE3d+pERQZB+PZchNtc2NICk1kopliMsCIcUFhSFCoEmgUOa6ydEyREqDqJIwIR5TEyjQRYiUJmrMEBUChBQXFIYIgTlmqJExQ6REiHgsQ6YEChwTpLRI195yhSGahggpKigMEQKv20Nlc8wQswaRUkEVhjwxQ83/55AgpYbb5+OsM0RIUUJhiBDoU2sDQBNTa5OSQXGT8yRQSP2fLkKkVNi4ox7n/nUW1tXUARBSa3MMEFJUUBgiBOaiq3STI6WCJ4ECY4ZIiXPfzM/w9meb0/+OR+kqSkgxQmGIEADq0papM0TLECkNGDNEiEyDMv+7CgJaRwkpLigMEQKNm1xzNrlGOoeTEiG4zlDq/xwSpBRYtWUXulaVSZ+5CgKOAUKKi3ihG0BIW8BTdLXZTY6WIVIqeC1DpqKr3AmS4ua/H6zBDx5/z/N5nNnkCClKaBkiBOYECkmHCx8pDYLrDKX+T2GIFDv3zvxM+3mMdYYIKUooDBECeIKGXGEIABqZUY6UAN7U2oaYodZqECEFoiym3xplYoZaszWEkJaGwhAh0MUMxdJ/NzGjHCkB1Jgh1U3O/ScTKJBip0yxirpkYoY4BggpJigMEQJdzFBmaFAYIqVAYNFVN2aIhlJS5JgsQ64QRNdpQooLCkOkaKlvSlgfq2r6yukmR0oMVRfOoqukVNEJQ7FoBP27VgGgmxwhxQaFIVKU/GveFxhx/TQ8Nf8Lq+PV/V0sGklrxmkZIqWAJ5tcjDFDpDRRhaG/XjgGs649Dh3LUwl4qRAgpLigMESKkh//8wMAwFVPfmB1vBoHEYtE0prxRqbXJiVARM0mx5ghUqKIbtIA0K9LJXpVVzCjIiFFCoUhQuB1e4hGI2ntYBN9IkgJYB0zxOFAihw1gUKnipRFKBpl3BwhxQiFIULg1fTFIpF0GlUWXiXZsmrLLiTaifTgqTNksAxRK06KHdVNrlNlShhi3BwpNeZ9vgVfbN1V6Ga0OBSGCIE3DiIei6TTqDYyZqhk2FLbgGkL1uXFNfKFj9biyDtew3cemZeHlrU8ngQKyobQTb3dTmQ7QrKmTHGTcy1DMVpHSQnxydoanHnPOzjiV68VuiktDoUhQuCNg4hGImlXiSb6RJQMX7/nbXz30Xm4d4a+An0Y/vL6MgDAK5+sz/lcuVBb32QV5+NJoKBYhmgpJaVCuaAIiEYyMUTRtDBEaYgUPx9+sa3QTWg1KAwRAq8PeCyacZOjZah0WLapFgDwwoJ1OZ8rqppaCsCC1dux/00v4up/fRh4rFp0VY0ZqoinChHXNVIYIsWNGDNUHo+m4+XoJkdKCXVNKGZCCUNTpkzB2LFjUV1djd69e+OMM87A4sWLA3931113YcSIEaiqqsKgQYPwwx/+EHV1ddIxf/rTnzB48GBUVlZi/PjxmDNnTrg7ISQH1MUtGomgrNlNjprw0iMfgoyana0Q/HnGUgCpVPNBqPccV4LIK8tS4yFM/S5SGvz97RWYeOdMrNteF3xwO0CMGXLXAUC0DLV6kwghLUgoYWjmzJmYNGkSZs2ahZdffhmNjY044YQTUFtba/zNY489hmuuuQY33XQTPvnkE9x///144okn8LOf/Sx9zBNPPIGrrroKN910E+bPn49Ro0bhxBNPxIYNG7K/M0JCoK5tFfFoxi2IK1/JoSYTyO4ceWhIa+JJoCAvD5VltAwRPTf952Ms3bATd7y4qNBNyQvi+Bfjh1xrKS1DpCRob2tYDsTDHDxt2jTp3w899BB69+6NefPm4aijjtL+5u2338aECRNw7rnnAgAGDx6Mc845B7Nnz04fc+edd+Lyyy/HxRdfDAC499578fzzz+OBBx7ANddcE+qGCMkGdXGrKo8hlk6gwM1fqZEXy1AbWElyaYMaM+RahuoaaRkieuqbimOuFNcD0WUunVGRCjJSAhR+BWs9cooZ2r59OwCge/fuxmMOP/xwzJs3L+32tmzZMrzwwgs4+eSTAQANDQ2YN28eJk6cmGlUNIqJEyfinXfe0Z6zvr4eNTU10n+E5IKq6OtQHsskUGDMUMmRDxe3NuAlFwpP4WFTzBDd5EiRI8o6ooU0wgQKpIRoC67erUUoy5BIMpnElVdeiQkTJuCAAw4wHnfuuedi06ZNOOKII+A4DpqamvDd73437Sa3adMmJBIJ9OnTR/pdnz59sGiR3uQ+ZcoU/PznP8+26YR4UBe3DuWxtGacbnKlRz4sQ/lwtcuZEE1Qx4AxZohucqTIERUD5XHGDJHSpA2sYK1G1pahSZMmYcGCBZg6darvcTNmzMBtt92GP//5z5g/fz6eeuopPP/887jllluyvTSuvfZabN++Pf3fqlWrsj4XIYDXMlRVHk/XWWFq7dxZs213uyk+CuRHkGkLslAY1NfjiRlqtgwxgQIpZhas3o77mtPiA7K7qJtXgW5yhBQXWVmGJk+ejOeeew6vv/46Bg4c6HvsDTfcgAsuuACXXXYZAGDkyJGora3Ft7/9bVx33XXo2bMnYrEY1q+Xa3GsX78effv21Z6zoqICFRUV2TSdEC0ey1AZ3eTyxfRP1uPSv8/F8fv1wV8vHFPo5liRnwQKhZeGwrRAVQiobnJMoECCKHyPz52v/PFN6d9iZjm6yZFSog0sYa1GKMuQ4ziYPHkynn76abz66qsYMmRI4G927dqFqKJhjMVi6fOVl5dj9OjRmD59evr7ZDKJ6dOn47DDDgvTPEKyxmsZiqU140ygkBtu8dGXFxa2+Ggo8pJaO/dztCZqzJCaQKGCqbVJOyaZdPDBqm2hE4CU0U2OlCjiGlbs1tBQlqFJkybhsccew7PPPovq6mqsW5cqTNilSxdUVVUBAC688EIMGDAAU6ZMAQCceuqpuPPOO3HwwQdj/PjxWLp0KW644QaceuqpaaHoqquuwre+9S2MGTMG48aNw1133YXa2tp0djlCWhpV01cRj2YsQ0U+CbQ07fHpFUudoTBtUMdATI0ZYtFV0o556O0V+MVzC3H08F74+yXjrH9XrssmR8sQKQHEbKQJx0G0KGy/ekIJQ/fccw8A4JhjjpE+f/DBB3HRRRcBAFauXClZgq6//npEIhFcf/31WL16NXr16oVTTz0Vv/zlL9PHfPOb38TGjRtx4403Yt26dTjooIMwbdo0T1IFQloKdW2LRCJpyxCLruZIO9w3lGKdIVXmL1Ms+q5lqGZ3Y2s1iZC88eDbywEAMz/dGOp3opsc6wyRUkJcBhNJB82e0kVJKGFIdaPQMWPGDPkC8Thuuukm3HTTTb6/mzx5MiZPnhymOYTkDd3i5mbTamTMUE447VAaKsWYIY9lyJBae+7nW/HblxbjRyeMyLV5hLQa2ebBufbL+6b/TscMUT9GSoxiVwDkVGeIkGJB5wlXZpFNrqauEbX1TS3VrKKgPc6h+ZBjCi8KhUN9T6bU2gDwx1eXtkaTSDujLbiGmsgmm+X3jtkLIwd2Sf+bbnKkVGlP2WCzIes6Q4QUEzqrpxtAbrIM1TclcODNLwEAlt12MqLtzS+qlWiPG4fSTK3ttQxFIhkhqbKYfSRI0ZPIYh6qUvp8rHlQt8MpjZDQiMqNYreG0jJECPRhLek6QwZhaENNffrv+qYinylyoD3uG4olgUIYVGGoLBpFB2EzSGGItGeyyYalzgPumM5GsCKkvSF2/2Kvt0hhiBDorReZbHL6SUC0BLVH60dr0R4fTRjL0I66Ru1Gqy0YCsPIY7o6Qw9fOh57dO+Av104BhXxtr9crN62G996YA5eDxkkT4qfbAQYVaFBNznSEmytbcDsZZut4vILRbErANr+6kZIK6BTGmbqDOknAXGzW+wTRS60xydjK0Qs3bATI29+CZc/PNfzXTaudr95cTF+9vRHBVkU1TEQj0Uwes9ueP0nx2Lifn3ahWXop//6EDM/3YgLH5hT6KaQNkY2MQ/qGGadIdISHP+71/HNv8zCCx+tK3RTJEShv8gNQxSGCAH0MUNpy5AhtbaUg58Z58y0Q0HR1sXt0VmfAwCmL9qgOUf469792lI8Nnsllm2qDf9jDWGaoI4BNZucmEChrbJm2+5CN6GkaQPGUCOiMFRT14g3l2wKFJBU6246tTalobyxoaYOuxtKu5Dzpp0pl/sXP267wlCxK3zb/upGSCsgjvNfnL4/gEw2LVPRVTFlNAuzmmmPT8bWxc3PXSZszJAojNQXoLCpei9q8Hi5UG+lLNY2t70ch0TlPx+swQertkn9+7y/zsb598/Gg28t9/2tahmK0E0ur6zZthvjbpuOw2+fXuimtGscx8Ejsz7H+6u25fW8ojWo2BUAFIYIQWZx++1Zo3DhYYMBiG5y+o2puB5ycTTTHh+NrYubn2Y5rJtcsgX6UxiBTL2VDuWyMFRdWZb+u1uH8pza1VIUe/pXEo75K7fi/x5/D6f/6S1pY/fR6u0AgKfmr04f99U/v4X5K7dKv1eHD93k8svbn20GAGzdxULOQPaKw1c+2YAbnlmAM/70Vl7bI1mGirzTUxgiBJlBXx73ar9N2eTEiYIaaTPFXHTV1zIU8priuQohQKr30qFcrrxQHo/i75eMa80mhabYF2wSjqUbdqb/1rn5NOu78I1738F7K7fhzHvelr83xAy15UD39kS8LWSZaUNk268+Xb8jzy1JITaHbnKElADuHkpc+9zU2o2GyEFpomDMkJH2OIfaGlT8LUPhrikFq+bLMhTiWPWS5Zrscf27VAIwW0sLTbEv2MVKSwkXomuPbqy6wo2rzFKboY5hV3ii0J0f1LjEUmfxuh343cufhi7k3lLjR5xP6SZHSCnQPM5FTaCrtbKzDLXs5jCZdPDz/36M/3ywpkWv0xK0x/2pvZuc+bvwMUPC36F+mRt1jangZRsBLKj2VqEp9gW7WPjH7M/xj9mp5CNPv/cFDvz5S3h76aaszrWltgFvL92k3RAGCcdB41wtpJ1xk2M/ywcUhmSWbNiJ309fgl+/uDjU71qqOzKBAiElhjvoxbm5zN34GQSdRIDWMZ+8+PE6PPjWCvzf4++16HVagvYyhYqbqfwkUNCf2+ZcedtsBdzHjc8uwD43TMOidTVWC6qrIDBZSwsN3VVbH7Fv28j/NXWNuO7pBbju6QXYUdeIHz7xAXbUNeHH//wgfUx9UwIrN+/y/Pb9VduweWe99Nnxd87EuX+bjec+XOs5Pqg7BG3GvXWGXDc5//MSO8TnX4quhwtWb09nJBX54Ittoc7TUk9OHD9/e2N5USubKAwRgszmU1z83GxypjpD4rzQ0puwjcoGoD3RXhY5UaC1ter4CS2i1tlGWBYPaa1n9vA7qYV4yguLMHv55sDjy2gZIgphFUF1QhplcW4VrTBf+/PbOOrXr2HO8i3pz+5+dQnO+NNbuOrJjNAEAJtrGwAALy9c77lWUH8IUnp43OSa/10ILfmsZZsxdc7KVr9uSyLGDJWi6+FX/vgmrn9mgefzsN2rpSyV4jr0r3lf4L8ftj/PFFviwYcQUvykY4aEzzJucqaYodazDLUTeSLvJJJOq7lSNCXDabgB//cuniLhOIGTrWwZsrt+EBHLqKGZn260Oq5MSDfvOE5oV8CWhpah1iesYCAeLc6hXaoy2Qo/XlMDAHhq/hcYN6Q7AOA3L30KwNxXdRvCoE1iUP/1JFAIcJ1uSc7+yywAwPC+1Thkj26tfv2WQJzbm5IO4m2/rnOrELZ3tdS0pyoTWipRQ1uAliFSMJJJB4/O+hwLmxe+QuA4Dv72xrJ0fn45Zsh1kwu2DLW8MNS6i28y6WB1ngpYZtv0p+Z/gQNuehFvLskuliAsSclNrvUtQ44gc7fE685HH4oLtYZMFtNCUux+7W2RsB6T4ljYUZcJFO/aocxzrO51Vlfq1Qq6Nx807MJahvp0TiUQWb1tN6Z/4rVEtQartnjdB9sr7hoLAA1tNClLQdB0/E1+3iEtlYBEOa2tcq09QmGIFIznPlqL659ZgJP/8EbB2jD9kw249flP0v8W5mbBTU4/Sbdmau18n33Tznp8tnGn8fsf/+sDTLj9VTz93hc5Xyvb1NpXPfkBdjcmcOnf3825DTaI79DWGOWbTS5qd1z6mJbIJifcRz66qFhstaWThqi4iR78aAtuciZLcrESVgAV59PPhY29rQLCeJymGUH9IWzM0ICuVTh77CAAGQtVXWMCj8z6vKiElNZCnCPbquttIVCfxKOzPseYW1/BnS9/qj2+xSxDytgu5nwXFIZKlJ31Tbj2qQ9bTeuu49N1hTe5qgKBuPi58RGmjWxrFiTLt+Ln0Num47jfzjQu4G4xwj++ujTna7UXZX1SEobym03ORm6Q3ORy7E9/ef0zPK7EF3yytgY/fOJ9fL65NuvzlomWoabWe7E3NSd6+GStvxW50G5yv3lxMfa76cWididRkWLtLI4XLYri/LNTk07YHUJJjaJixaZaTFuQSZqgU7oEKRWCxrnu2z16dAAA7GqOffrD9CW44ZkFOOF3r/uei/jTVtP1FwK137pxRX+YvsTq+JZqh5pdsZigMFSi/HH6Ejw+ZxXOv392wdpQWWbf/Z6cuwq/eXFx3t3F1M2TLmbImEBBmLtbPLV2C933GwHCsK1Q4Ed7SUObTcyQX39UY4aCyFca01VbduG2Fxbh2qc+ktpw2t1v4un3VuPSv8/N+txiwLMuo1wy6eCcv8zKe9bDvzcnerjrFb1mtK1w92tL0dCUxB3TFhW6Ka1GWMFd3PTuasgIQDvrvMKQOwwSGhfWY34zA999dL7n2GkL1mLinTPx8ZrtFm5y4WKGAKBDWSqwZXezMPT6kpSFaLeF5ZLIiNMchaEM4RMotEw71PP6jZc/vbYU37jvHSsLfluEwlA7xHEcLN9Um5Ng8LkmbWlrU1mWiZYMupef/OtD3P3aUnzwxfa8tkGdgKMay5BJ0GlNy1BL4euHjHBFO03k+mRaK0Zf3NTZDi1bocVGWJaK+ObQn7bvbhSu603KsHSD2T0yiEgk4lt/a/2OOryzbHNRZx2yIVclwvZdjcEHtRHEMWDTa8V+U9+YGRd+hSZtMj268/F3H52PpRt24uf/WRioiAlyk4tqdkgdylMxS64gJ97P+po6PDrrc0nIyzftRLdkhSwMFdGN5Yj6joOmk2xd0YMI4yb36xcXY87yLbj4wXfx0FvL253bKIWhNsKuhia8snC9lVT9m5cW49jfzMDdObgwtQVtvbuoAEBdo51WaEddfjcJ6qYzqkmtbVd0tX25ybkECUP5sAyFmacTSadggmVTNsKQT1vFr8K6yeXyDMT7yDYouTxuXhpcJYFOk9vQlPrMcdpPSvWWIJdx8/iclRj1i5dw38zP8tiilkNUItj0W7FP1jVl1rsdPsKQGs+ns0ap3S0WjQS2x31PJqFI9x6rylNKPNdNThy3X7/3bVz/zAIpDpWYkdbQErMM+c2P6jdBU2lLTbVeoSx4Xntn2Wbc/N+FOSndCgGFoTbCVU98gMsenoub//Nx4LF/ei21SP7WEExnQ1swZIjB2LZCTl425wKqNko8vZvpxpxAIfN3ooW1WuKikc9N5sYdAZahVpSFkkkHJ971Ok686/WCBMInJCuK//V/+q8P8aMnPwjYbIVze8tX3aqEIHllu8HoXOnN7OXil1jEFYZS7cj/O2wv8pVNOvi3P9uEq558H9t2NUifX/vURwCAKf9rH652kmXI4v2IfbJOsQypc9sTc1fhtcUbpPk1GolI1s/0tZVzD+peZREzJP9fRbf569AsDLlucWI/X7UllYHz1U82+F43LMWqWBDfT0tkk1uwejvumfFZm3TB85vjw77vfK+XiaSDP89YitlCnS8g3P6rjVVdCITCUBth2sfrAABT313VSlfMffD87Y1lOPWPb3oWc1vERaRG4y/ukpRcJLK6lBF1syieX6ypokOqM9TCi5V49nxuMoOEoXwIn7YT++baBizdsBNLN+zEliz7VC6Iz9WvxTvqGvHE3FX49/wvsL6mznicaA2yWazCathN1AsCSbauJ3/71hjjdxn3Ue+5xWsXOplBIbEJND73r7Px1PzVmPJC2xZ6ttY2pAQSw/tMhOy3Yp+sFyxDSUcfd3Pxg+9K82skkim0KuI4kMoB9KqusCi6Gmk+p8ky5P2sqky2DOnuOd9x5u3VDTsIcWloiWxyX/njm/jVtEXp4tJtCT8BLbybXH555r3VuGPaYryu1PRy27Fqyy78/e0Vvp5MrVUfMF9QGGrHVPi4sgSRj7n11uc/wUert+Pemcuy+n2j0AhdJqHMcZlJI9+WIXXDJrvJNW/6jG5ymb9bM5tcwnGws74JH32xPWeNYWDMUCtahsRribfVWrUNskltLW7+VUQ/bqs6Q3nqT2IcRjYa0d+ffRAOGtTV+H0msYjGMiR81hKuuO1lSxgL0WU/35J9dr/W4Jy/zsLFD76LR95Zof1eFPptlEKNBssQYF4H1Ji7LVphKBVLm26XE7zOuWPUtG/zc5NzEyjo7jnfxYglF952MwqCEe+lJZMQBWWhLAR+2TjDvuMwc+2idTWBNbKWGspuuOPk+N/NxE3/+Ri/8/FOyvderaWhMNSOERMQhCWfG5XdWQaLilYZPze5JsVFwsSqLbuwJGRKW3VDJ8ZK+G36AHnD2vJ1huSN9Sl/eAOn3v0mXsnRHWPzztSm4sMvtuHemZ/5xlBli21XE69UiAVfsgz5XF5csxt8hKGwbm/5ihkStet+7TMRtJHLxAx525gPN7kVm2pxwzMLtEV/W9IAm09XpDDjppXLNYVmUXMJhH/N99Yc27yzXlYiWFmGMjesKhNMcbDq2NysUeI4kIWpRNIJXOfc85rel05IcmNd025ymnFg8/o37KjDw++ssEq20BoxvqKVrrWQ59Lc73FXQ5PWWt8WvQz93AI9lqGAc4W5v5PuegOX/n0uFqwOn4zKHSeuEuOtz8zZaNuZLERhqD1TlZMwZHfc1DkrccSvXsXSDWYhI1sXMVMlchVx8TRp8BzHwZF3vIbjf/d6qExM6maxMp55pn7uQO41XRItvKNRrQZuNsD/fpBb1i733Z1291u4/X+L8I/ZsjtBPizdtgt52IQD+UbecJnbLPZ3P8tLMqSlKV8JOVyNNeBvuTIR9M7T7qMBMUPZvsNjfjMDj8z6HH9+LfcaV7Y8OXcVDrnlZby3cmtezhemHoc6f7ZV75Laenmz/OiszzH61lekdOd2lqHMMaqbzUzFLcdFVIglHUfrJpc6nxgvF5yMxW1LzLBz84sZSmeT01zDZiN43dMLcOOzH+OqJz4IPLallW3TFqzFiOunGa1/ttQ3JTB3xRY0JZJoTCRx+p/ewk/+Zb4/ec7LfdI/9LbpGH/bdKzd7lWktDVs1w4g2CIurle2Sh2/ouumU6jjwe9StAyRViNMnR4V2wFzzVMf4Yutu3HNvz8yHpNtbKK4KOpqTOiOM40vcdO3YYc5jkNll7IYVwjP1C9QHFA0/62YFjRXlzx54pS/m/+5vBnMh7uHraxsqrPTWnOqnEDB7jhfYSOk25ssDHqPX7imBis2BbtUiZah7IQh/wcet7UMZaEkEd1ZdjW0nqb6J//6EFt3NeKKqe/n5XymzbUOb/ratrmJUF3Y3EKQz76fUcjY9HNx0+sKQwO6Vvn+Xh2bJjc50brRlEwGBuW75zU9cj83ubrGJJIG65PNO3x5YcpVyY0X9sOU9v93L3+K+99cHvj7IL73j1S9phueDU7g5MfV//wQX7/3HfzulU/xzmeb8cGqbXhyrtei6CI+uXwkOXBjj2cv2xJwZOHxjRkKeS5p7bD8cVyXN969vmHuVj+nMETaBK3pJue3qco2k4moWa7xc5MTFk/T/CHWqHA3azbsVjZc4jMti2ZihrbUNuCx2SuldrZmnSFTkHI2VxWbqrqj1SrPI9/zWTLpYFdDE866920MvuZ5nPC7melNlnSPBag5YZtNTjzOr9Bi2P7h+FiGNu2sx8l/eAPH/GZG4HnqJDe58AJFsGXInGWxPkc3uTWCa1zv6grNEa3njpoLPvsMD57Chm3UNLRLEYZ0c0PQslLflJD6p9tfXPdk0+/ltPeOVlBOOnK8XFPSCVRSuWuL6Znr3eQya8TuxoTeMuR71RTjhnRP/x3kzaC7xsrNu/D76Utwy3MLc3bxzJcb2X+aPRX+9sZyqz2G2O581hlqD/twX+EvpJuc7VojfueX4MB0BrUf+r3jNjqNGaEw1I6pKs9eGApf4djObSgMtgkUxAXNZEoXF8cwmzC10F9l3GsZakomcdnf38XPnv4I1/z7w/T3JktGSxA2Y5PtudRmq88j39nkko6DR2d9jndXpCxQn67fiX/OXeVpV6OFy8T2XY2Y9Nh8PDrr87zEezRZCpmmVMIerZnw9y3PLQy8vpyQQ75/G4uQS65uckFLb5kwLlQaEmJ2sPDvRI35aG3CWHT8CBczJN+nrg11jQksXFNT0BTLqqJE106/d1bXmMCYW1/BTwUvg/pmwciNzzT1GVVRodtIOlCE8YT+OBF3bTHHDHk/F12pdzUkDNnkgt+/KOwHeTPoMk3uasyMlbYWE9OhPGblVSA+unymv853AouWwC9GKuzcKR7t91tRERH3E4YsxmEQ7eEdiFAYameIk6I4KYc+T8Bg276rEXNXZEzNvsUl82AZ8tu0iZOkaY8sbqLE44PGo6rZFy1DGTc5B/NXbgMAvPBRxqUhX9m/bJCsYznWHJJqFinfeYWh0Kf3IF4j4Tio2S1fw333YS0pb3+2Cc9/uBbXP7MAMwyxBmGwreVk6u/qx+K/Zy/fgg0+abjV66sauKYQwnDubnL+32cSiwS4ySnt9LP+ukjCkOYdLNmwE797+dO8F192yZdrR5i0sjZV3i96cA5O/sMbeOb91bk2LW/orCl+SqGFa2s8saFu/3Stjaafq25yWmHI4ybnBFob3HFlrjPk/SwajaTjdXcbhCGbbhRGmZYImBtbWhkXlg7lcSvrWEul1m4P2/AwbnJBgoWf67uIKAypc9QXW3chkXRQ15jAPMVd3kXte+61dOslLUOkRRFjXHKxDAXtNU+9+018/d530v/2za6VhwQK9Y3miUHaCBquJWbkCaNhUt0txHTlZQG+LlI2uRZ26xLPn6ubnPQIVcuQx00uvzFDjuO1+rj3E/Z5ivEAYbMI6hCv6delTcHM6jhQ/x30LP2EQTlzoX//loQhHzc+E7YxQ7p3ZBKG7p35GQ68+SX8a545fgCQhXHdO/i82TXoty9lX3Daj1xc1MQNQRihypPBUdOGWc0xEP+YtTLL1uUfnWXITzFmsngBQFnzvGtjGXIcs5Aju2kmA8dKcDY5/edi4VV9AoXg9x9mvpO9I1J/iyUH2lodoqrymFIqIXjObImiqy75MlIkkg7Ouvdt/PCJ93M+V5g6Q0HYprevM9SBm7ZgHY741WuY/Nh8fP8f89PKXxW1r7tuxdlaR9sSFIbaGWKigVyKWgVZFFZu2SX9299NzvtZbX0TTv3jm/jtS4u1v1m9bTf++kamPpFfWk/ZMqRvh5jpSEq4YDxrCjVmSIw3imuKhYiPvDVjhoyWgSwuK1mW1JghNS4g/Ok9qGnB1YXffb9hn6d4nnz4m9tmfzO1zfObkE3yszSG2TjpYjLCEBTvUt48Rn767w/x2mI5tbt4PfF53P6/VGHRH//TP3PWzno7d9eP1/inhc12aszFTU5sb5iNgNpt/Ob1Qm8wRGu+rp1+GzHd8emYoZjrJme4rrDbcwyWoaTjyDW2ksFucu73YYWhKiGjnG5Nsul/tjGK6ve6cdEaqbfD0KE8JglrpvcqWcNbMGYoX49nwerteHfFVjz93uqsPWJcfFNr51BnyNZNThzL9878DADwvwXr8Ooic7kO9Z7dS+nGfaHnqrBQGGphPllbk84akw9EN5JcBmPYn/otcrp2TFuwDh+t3o4/GupGnPGnt6Q2+G3aTFYRkVqDm1wQfhWUyzSJGGLRCJ6a/wUm/WO+pIFv6dSn4sSVq+Alu4PJ37VMzJB8bfX9ZCxDmc9E65GpBbYprm1pkjYn5uNMi436sSc9quNg8bodRncxPze5MMJQrjFDQVptV0mws74JFz/4rvRdQ479VFT2+C3qbq0XYxsNEp3jOPj1i4uMFqqwlqFVW3bhraWpWhuiQB4ih4smtba5DYXeX7jrz6+mLdLGeYZ95WnLUNpNLtgyZIwZcmSl2vMfrpXcmv3Oay66qv/cdac2J1AIaRkKeHA6ZZjYF9qaZaiyTLYM2aTNznUOT2apjAiDeFq/5Dk2+Cnwwgpv4uGOz2NUlQUuttOe1zKUQvd6Cz1XhcV/RSE58+XfvwEA+M/kCThwYNecz1cb4FNvS+gAPXWjF+C207mqLP33zvomdKqQu9rGHXLRPF9hyBAvIyK6d8kxQ/4j0k87owswjEYiuOrJlHZbLO7W0nWGGjWLIZBd9itxslR/rbrJhcmKZbye8Hcy6V303EVBzhoYfF/5dlM0pa9VMV3L5E/tMn/lVnz30fkY0LUKb13zJe/1fSxD4jMLSi6R6yId6Cbn0ykaDJYhW8T5zV8Y8ncRNjVx7udb8afXUlrQr48e6Pk+jBADAEfe8RoA4N/fOxzD+nQSru//DP8k1FAKk1o7F2+AbFD7obsZumfGZ9rjP1i1DdMWrMVJB/TzfKfb7Lp1gVxhyPTOVUWFWRgKNw9nBAv7OkOAkPDBcDmbjaA4jQQpNnUJFOTv5X/XNSaws74JPTvpMjK2POr4ND2nZB4VWlI5hpzOZEYUcnfWN6FjRfZb6EafvppLgitfy1CT3jJkKzzqFHyAfg9IyxDR8vGamuCDLBA3Orlog8L+1B0En67fgf97/D18KhRh1c1h4mS4SnG50+GXAljMumJ2k8vOMuR3rG7jIQ7w7bszGv6WtgyJqabVbGaO44SyEvolYPDEL7SAZUjNouMKkuJ8aiPciM/cJvtcmPP5JlCw8H/X/fu/H64FkHIRDfq9+h7CpKze7RN/Z0PQfluMq1ORY4bCX3tng102uWwtQ6IS5vPN3gx92brJvbdyq9Rn/cbNys278OsXM+7Danfye/6tvcFQi1LbzDPffXS+x/0Y0M+RriXHzVBoOrtqGdJl4ko6TmhhyJ03TEKm6XG7x5ssHnYxQ/r4DR1NkvKxWYATz6V0ouN+OxNjbn2l1YqPLlpXg1/8N5MxM+Uml8H0nMSPc3V1FvtISw0T0fLolwE3iN+8uBiXPTzX+L26/gTdjuRibe0mF/55qeuyeynd621txU2uUBhqJfzcsVQ276w3bsakQMpcJo+Qqgd3o/aN+97Bfz5Yg3P+Mks4lfdc4uStxh/pyN0ylJmYxIUykXRw30y9FhPwn4AjkUh6kXYRx7c42HP1Hw5C3Oyrgf5fv/cdnHDX69bCsV82OZX8JFCQBTmTZciUMcnUBvGZN/qkKbXFNjGFOWZI/rd6VFAyA8dSGAoS9utyLFYatOH2q2/ml03OBtlNznxcx4oAy5DhFsRnd/SvZ+CdzzZL32fb3x1H1rT6obpJqs/JbxPx5tJNmLO89QpKqsKQrTfCK594XcN1mnD31tOWoaResSMrKvRjIJF0QicMcZVMZje5AMuQ4XmEjhkKGCu6+CLxFxt21EmeCq7C5c0lm4IbkgdOuusNPPDW8vS/K8ti0g7exjIUNH6aEklc9OAc3GmIQ5YFSrtxXNeozwZoQpyHVZfyMNz9mj58wCXszGkbfya6yTWE8KAxndv9lz5myOqUbQYKQ61EGI3V6Ftfwd2GWBsbwcAGv/GvE27cy25rLg63VSgSp2uHOLnbWIZ8s8nlGDM05X+LsG1XA37x34VS4HUi6QROhOrGRHR/Eb9r+Zgh/WTXlExi3udbsXTDTiy3rEWjxgx5gyJFDXe2Lc4g9g//mKFwlh5ZW5q7Zci66KoxZkj+XFWABLmvia/BvTen+XmZNHoqdY0JLFxrZ4U2KVyCXrmfICIusDm7yfmMKV0mTfF4k0Chbu7/PV+OHcpWm5l0HOt7V78Ka439xn3v+H6fDZ+srcFVT77vmavVxDa2G8fNO+s9nzX6/FZMra17dqIVxYE+ZqgxmY1lyBWGTAkU9L9LW4YMY9HGgidZwoPc5DSJBsR3cdJdb2D8bdM9c44u7rU1UN3kjHOm8Ldf/wCA1xZvxIzFG/EHw94oEdLSsaGmDmNufQXfeWRe8MHNbBL6dS6WoSDCTp1+tQNFTAkU7GOGFEuxj5sc6wwRLX6bfR2/fVmfOjZIMHAcB+u2+9czAfxjTXTWkrDZtcTJ3aY9ttnkzMKQmMzA+6yve2YBHnhrOU75w5uob0pgwertVu50anptcZETY4pM7Vq0rgb/mP25Eo/i4Nn3V1sLL4B8T7aB/ibUx6PGTYnnz4dbjrhI6WKG3OtJbmIWVk/JMpSHBAqy0OZznOFL8fPrnv4IbyhaWZ3rkIgcF5C6nyufeB8H/+Jlyd3FT/B7/dON1ou06T6CFjG/lP4NhtSttuy0jBnSBag3WQhDQW3K1k0u6SgKC5/rmPzuXfIRpxeWM+95G0/NX41vKxtDVbiw1TnohBK/GAkxZki3cd5am1G+mWKGmhSlgQ26ZAQiprHg9i/zGAq+dhjFZpNmbtCNj227GqX+pMuI2hrEo1FJ0jHNWWJbg+ZwVZGhIl7D5q4feGsFdtY3aa2YOp7/cC2umPp++t/iniPfhFUk2cbb1il1uFxs13lTXKzu9dIyRLTU+Wz2TTw135vxKKj44q3Pf4JDp0zHfz9Y43tuv0VNp8FOOg6e+1B/Tt0kJbbNpn6Av5tcsGVIqjOkcZlyMz4BwPVPL8BX/vgmHp31eWC71MVEnLzFDddrizdo23bSXW/guqcX4Kn3MsUS//PBGlwx9X0c+5sZgdd3MW20stlwqhOtKqjLsQ8B50o6eG3RBt+Col7LkHx9d3E3ZVcyNUGKGcpDAgVRU+YXM2TjJveP2d56MHWN/ueXEyik/v/s+2uws74Jj89ZlWmnzztfsmGn8TsV0wYs6J13KDPH6+TqJie6u/q90kQyiR11jZKiRdwQmIQhdcOlHpWtIJJ0HGVD4n+siPoeRIEsm6LKIq7iZdE6f2uhW2/tE8WqqCqpmpJJO0u/ThjyeSjl8dQ91zYk8Plm7/l/JKRkT1nhNAq4RHjLkDvms7UMmcaQzT5QvAU/5U9NXSPOFtzS3Wvq1vCyWESaC/2SnbQkjuNI85nZTS7zd5CbXNC8ZKvMcglKzw+k5rOrnngfT7/3Ba568n3pu1zc5IIIO+ptvRrENUjOfpmlMOTWGdK6ybUvaYjCUCsR1jIEAFc9+YFnMQzSANz/5nIAwM3/+dj33LKrlHwenXYt6QCTH3tPey53AXIrFycV97MgjY54jsXrdniCPhst3E9ELY1O+BKTHfyzOa3urc9/EtiuuOJmYFpoPl2/E4/NNgtX8z7P+Pln4/NvEgiziVVSn6EqqIsboCArwX8/XIOLH3oXx/12pvEYte0ey1DCXdyDhV4R0XUmH5ahNUJiA789qOmZB21cg+r/yDFD8ve2bnI2Yy1zPf3nQZnQ/DK51efoJifFDPn0gaakg8OnvIpDp0xPC0TS4m7ot+rzUa+QrZucWgjU797V21L/LT5/WyH/obeW4/nmBB0ibyzZhCumvo+T7nrD6jwqdcq69dHq7ekMev6/S/XXZNLB0g07Us/H532Kc+kJv3vd99yOo+/ni9fvwPurtgW2TcSdm8LWGXLbm611FbBXav3t9WVai6uujyUdeT53hUwRx3Hw0sfrWjS5ggN5g2y2DGX+bkw4vh4iQfOS+C4mPTYfi9dlkjzpPGEWWiS1enLuKjz13mr88IkPUK4kjsnWTc5mzVZfbVB3UmPqTJjc5Gxd2jyptZv/qRPmKQwRLX6D3A/VSmNbm2BzbUP6b8dxcNsLn+CJd1cKn+nPCejdefwGsLuxu3Lq+zjznrfx8DsrpInQThhKYNWWXTjxrtdx2JRXpe9k10D/NgDmtKvZUKZMwKKgpSrd/vuBdzPiIm4qTI9yhxJY7ThOWogzuQpKrgGWc4+6LqmCutjWoFPOWLwRALCjvglvLNlouJ48Uavv56n3VuOLrbusFk8R8TT5SK392caM26LfZtY07oLWOHEs65Qjupgh3W/9BL8wsVOmjVygZcgvZsjCMvTW0k2486XF2u9NRVtVmhIOdjRvRmYt29z8mTg2TZYh7znlGLns3eRMShs1KYAqNKv/FgU5GyF/6YYduPm/CzHpsfme71RLT1hUxZLfHCfivsfbpy3CxDtfx29f+tTKTc66XVmupyp+ggXgIyQFxAzZucnZCc87lE23u/HUaeMdx5E2vLr2P/N+yh0yjGdCWJKOo4wB83Eur3+6ESOun5YuAKoi3ovWNV8JITjr3rd92yjukUyIMUIVcXney9YyZBMP66dYm3jnTI+Xjvg8fN3kcqwzFKboajuThSgMtRbZFD8EMgkLXBot/dJF5q/cir+8vgw//fdH6c9ETYnakU1uciZcQW/ax6kCd3dNXyJptutt3OQak5jxqX4zbeNbnW8rgYtqGfKbdCr9NObS4u29h+c+XIORN7+Eu19dkv7s1y8uxqifv4Q3lmyUr+uTdcwGj5ucsrEIWkxFRE36BffP8bjQOI4jW4YMLi7n/222uW6QpgkrN+/CI7NWpP9t44oZxGcbMy5mfsKzqQ8GWUJETaLObdbvvYqn9lOChHEXNLr4BLxzP8uQVGfI0M7z/jYbf3h1KZ4RXEfTbVLG18Yd9VpLqvgM3M2izVjQzQ2SgiNrYchsGfreP+Zhwq9exbZdDc3fyb/1S6BgM5dt2mne1OWqnVWFdtt6au6c8pfXlwFIZc/yE9TLNBYM//PnZ45PBAhDpscXD3CTs0ugYKfYVM/lXlO3YU44jvTOdPf1yicbAHitfvkk6SiWfoukM8uaY2hv/98i7bHiht2UTVCkps4srATFb2bal/lbLSmQrTBk6ykz7/Ot2jlt6YadHi8dU4IllTqDUs12nvBahpoFc007wxawLjQUhloJv8nbT6jZukte6OTaBN5z6mqA7BRcyNzO6+fPqxeGjE30DO5tuxolrb3t4F+pqfsB2AmA+Y4fcfELQFU39e99vhXfvO8dLNXEbUiWIc3juKZZUP3NS5nEGX9uLmz4y+c/kVOqGwQy131k3udbfP2vvcJQ0vjvN5ZsxPF3zjS6n6ipx381bZHkkuh1CXK0GuIVm3f51tlx2bijHm8u2YQv/XaGtAnU3W9tfRMWrqmxirtwHAefCe/N183JIoGCjh3C4qx3RbUTcv02yKHc5IRDH7xobPrvoIWxyjZmKOC5f7HV66Yj+74DR/zqVW32NPF9u651Nq4iupihIN95v1IHYlubJOtt5rsXP16PtdvrcO/MZZ62p441n7shkTQU2Qy+VyB37aw3ZshubtVttHVKEBc1UU1wu/InDKnxLSKmsRCUQMEqtbZiPTSh9slM9k3vsUkn2KU2bPrxbEhlBcz82yRE267U//1gjRQP2ZBIYmttA17/dGP62YWJn10juAjqiqvr2qfuraYv2pBVTJ/N/mRnfRPOvOdto5UMAFZsqsVfXv8MuxqaPPOmjq21Dfj99Iyydf7nW/HIOyvgOI51kVpjam2dMNS+ZCEKQ62FX5YbP7Ppdj/LkKbT9+lcmf7bHajiIHa1oNLGS40h0bnJ+VqGdFqazGe2bnK6wFlA3WQEb0TFgoY6ggrpifgt0uqmfkd9E2Yv34LJGncV8f3rU8ean2+v6gqpj8gat8xxjuPg+mc+wpn3vIPbXtBr13TX97MM1TYksGTDTlz60Lvac6kBus99uBZXTH3PqDFKamKG0vciur0Znsfxv5uJ8++f7fled/zpf3oLJ//hjbQrnx/ra+pRK/R7v+VKvZbbb8Ksi7rNol+dIZFsBSXPeYTriW5KgW5yfpYhi7HqolM0qK5Dpk2veO6d9Y2ez0ybFJ0FURzH6uZ32oJ1GH3rK4HxhWrMkO76MxanNPJq7Ix6qOpirHun4nMRr+XJTJerZUh5/rbuqNlmk7MljNAfRFPSMa5vpunfdWU0zVO6bIcqtpYh9RU2JR3srG/SPoNk0pHmliBX1JbCceS44XP/OjttGRWx8W6ZsXgDfvD4e5LFqLEpiTP+/BYufGAO/jkvlVwmjJfE2m2ZxCu+ShvhOzVm6OM1NXhn2Wb1F4GEmaPdGHAdJ971Om57YRHumLZYUoyb+vLcz7dK/569fAtuePZjTFuwzj5myFB0VS8MtS9piMJQCyIuTH4TkJ+mYNtuc4E+nWWoZ6fy9N+uT6w4iF3zsDhevvvIPPxrXiZznc4y5DfRuJqm3tUVwvGZ720Gf31T0igM2QQmh9EK6U5x6NDu+Pf3Dvd87mcZWm/IoLZhh7fGhiwMeX+j3pcYzN+jY7kxViyhuBA+OTf1Hh94azk+XrNdazFRr++NGfK+f9Vv3UX3fGYs3oiLHny3uX2KMOSY+0NQ3wa8bqMuuo2Ba6ELyqwIyC5ygL/PtrqAVzUXIQ2TMEBrGbIQBgH/Dan7bNWFW4f4vMX3GLSI+dYZUmJ+/FL9q8oH9bn6Cn2iMFTndZNz/1ILnOqenSwgyd9P+V9KCPLblADNFs+A5DaLmgO6PZYhx3zfX/vz23h10QbPuXYb5hOvy13mb7VP22xE1XXLdsOpsz7k000un8LQdU9/ZFx7jJah5vFieoahY4ZCuMltrW3AATe9iPPvn+05Nuk4Ut/QzSNh049ng+PI/W3Djnrc9coSz3E23Wm+sokHUnsC9539p3l+DyMMiZYhx/FJiiP8rfO6WbMtuGyISpi+684VOuHaHZuzlm22yiZn+vzT9TutrTimbHK6c7czWYjCUEsi9hs/07SfS5PqJicF0gdk8NjV7B4n9kk3harYed9cugk/FlKX6oQhvw2YOyj7d63Stttm8DtOpmq2SqPkGmgY6FnEzrgM7FaFqd8+DAcN6ur5To0ZErEJwHQxaXIzn2X+TiQdHH77q+l/P/P+Gnz4RSYNqJx1Tf6dyCl/eBPXP7PAc63gbHLe92XKzmXS6M5sjv/SbfRMwr+usKAtfsKDTYYwVRjy607qPbmPxm2/zaKcTzc5Ma28+9w6+lhvXNx+GI143R39sHaTS6bqex06Zbr2WNc95aWP1+Gcv8zyuM351zbLXCcdM+TIG4Lb/7cIB978Urovqu0DUu/OL+lDh3LzvcptVQK4fdqu9n9Pqm2hDRt21OP7//BamsU5Woz/NFkt1eveM+MzHHLry1i6YQdUpKyHjaqbnN1Grk6bWtv8TMK7yeVvQ+8qkHSYpg63795kyNqqTpcNTUlfYd93/lJONsvHGpFIygkUCmUZ0tWLqtntVWTZzPL6vuT1PMnWMgSYvXPEsakmUAD8lWaO43iSIgHh4lttbimRdBTBWn+cSQmZdBz7OkOe5C+p/+v6Ly1DJI04OHUD2sXXMrTLbBnSLbhip3QXDHFAu8KQ38ShCy70c+Vzz1VZlulOokbWdvCLAeaOYWNsanc29XZcyn0EHjWbXLbUNfq7YInvKEh4bJSEIf9YpKnvrvJ8pj5DG8uQSaDw87cGvK4xaj0WEZt6Usbr+PQxm8KDbrzQXr06AghXZ8h9Nu7HNhs13Xzgp+EXEZ/T/W8ux343vohpC1JZvtyxZrOJd+ePWDSCWFR0kwufQGHe51vx0FvLPW5yj2nqLbm4z+3bj8zDO8s2SwoZAJ6itSLinFmrSaDgOEj729/63ML057p3I/YddR4Rhcr1NXV4+r0vsL6mzrOxTSYdpU6VsemaKu7y9zZ9X5yjxcNVwUp0fxHv/VfTFmHbrkb8alrKpVicA0/945vpv701wbK3DPmN0TDCOGDeJI4b3B3H79cn1Ln8MBZdDRgjoia/rjGBI+94FV+9R85u5ueqLqIGovspd9SYIa0w1IKJE8R2eC6tabZNzE1QX3Jj0cJk0txcK3tvmPq1lEChzLtP8FPYTH78PYy8+SUpxTcQzk3O5tik4pJoapPpXA6C66vt268zAJ1lKIVO0KUwRNKIndLPMqTrpN06lAGA5GfryczVvABv2FEnfZa+ZvOGSxQmJt45Ext31AekX/S21Sa7ljgXiRNuNi4NYvPETUa2wet++PmrZ1PBW/eLOp8MPzvqGmWrSMCk3mTYvJkW1F/8d6H0b/UwVVOo26gbsyoF+PqrtRh0RVfT3xk0pTZvwE+hYFN4cHmzy8VevTo1t9N8rCn7l/sObTYb+jFmpykWv7uleaN/5RPvA8jMJX6ubC7ufUQjEUmoDXpcOmHozHvexs3/XYjlm+zSkwPeTd2cFVuCmpxGSqCgEYbExye6DKqxWh+s2o4bn81o99U2Vwn3esof3sQPn/gA42+bjouVGLpUIdDgeKlfTVuEJxQFhV8tOROmGET1uuK41c3D7nsXhRExUF2dU6wTKIQsulpm4dZpw61fPQA/OXFEXs4FBCdQMP5OuJ2P12zH+pp6fLBqm3GOS/g8G/VSfpvMpONIz15vGWoFNzk4nrVa5+pl41qsL+Cb+V1jFpYhdb0w9WvxU90+wU9Wcet+PaC42OqKwpuwuaekY5em3XhdxwmMGXLDL7xZTh18sXUXLnxgjuc3QQqDtgaFoRZE7JPiQrRuex0uuH82pn+yHoDeJahXc/zN1mbL0JptuzH2l69IyQESSQfn/W02xv1yerqacpNGGFI78H0zP/NMBuJiGDblputzKy7iDRoztkhgNWmhzY0WG/5cLEN+/uphA3tNiAuQeAuPzV6JkTe/ZG0VAMzpi02/e+Ct5dKGKyiBgk5wNy3+Qe9xR50qDOkDqcvjUSW1drg+6LfRsnGT29lsyezWITXp+70BU1xGWhiyEP5NhY0z1zCfQ/dsXDcjd1wHWYYcx0n3w2gkIj2jQMtQhZ3rWFA/zrbAKSBvZnQxQ+IbFMew2tcXr9+BN5dmLFDqXNxReI5izZGZShkA1U3OtCG5Z8ZnHouX+pxsur7Uf3zmDp1yTMSNgzAJI+qG1tZ9dZcmxtDXTS5P8+ygbh0CFTRhMLrJBSjJxDHUURgv7nzYmEhKiYr8Hqs6HnUxqS5JR3aT08cM+Xew5z9ciy0hXMB1pLLJmQVzF5tlWzdXypahZqWv38k81lclFk55AT97+iNc9ve50lqlTXxkIcypx4Rxk7PZ13gtQ/rjTNd1EDznu5ZjtT1JB/inwc000s6ki3bW3PaFOAjEhej6ZxbgjSWbcOnf5wLQu6B175jalLnmxz++usRTT6Ip6WB2cw0Ot0NK9X2aF36ddk/VPoqaAZuiYCoJx5EmdFE7rluEgxYsOX7ExjKUvenf1zKUNzc5OdGBy8+e/shzbNAEKMWN+Qg5xuurbnIWliGTlidoc6T6TCeSjnZSrohHlaKr4YRbP+HJxgXHfT6uJcDWTe6F/zsyPXbcLmjlJhcQM1TXmMSVU9/T/lb3zOOxCJ59f3U62L660l9gSSQzC2jKTU4Uhvzb7iaMSLfbFMcXsFFwx1Y2QpGoENDVGZIsQzGzZUhFbbNfgVn1dzYZnfS/BVZt2YWFa1IFUm3mst2WliFRANEppdw4CNMc6M3aaDfPLtmwE7e9IGfg81NY+Lkq2/LwJeNQVR7L25wN+BRdDXKTi+iVC27ZgS/9doaUlMbvnYcZH4mkIymzdOcNmp8mPTYfY3/5Cibc/ir+9sYyq2uqqBt0IDWvfOeRuTj3r7PS86vNMNGnac985vYr3wycARZONZnFY7NX4pVP1uORWZ9njtHMu34WvfT5VGEom5gtny6QSNrNPUY3OSd4zo8bEoY4Pm7vdJMjaSQ3OWEC2rhDCd7TdFJXGMpo1r0dS8oG5VbETnoXP3XgV8SjnoEtDoawwetuW8SBopusRIJiccRn12gRmJyTZchnId5qyF4m0r9LZeAxUsxQwAoQaBmS6i7Z/W5Hvbn2j+rWpbMMRaMRJJIOvv+Pefjdy5laSEHPXbUMOY5JGIoZrVw2aT/9tM4xCzc5N4mE6wLmG7zf/N0J+/XBfv07pwXFcJYhXcxQ5prvLNuMZ97XZ8HTKSvisSiumPp++t+dq8p8r9+UdDCvOUtTNCJvuIKedywakZKNmAshB1mGUtbAMIKDi1jIOW0ZEs4jarZFy29QJi21P/ulERdxHLUemtXP0hx5x2s4+Q9vYENNXeiYIT9XWVFJ4PZLcf5xXQhVYcSds8Nk+FNxC64CKauAuA6coMT1ZGsZEpeRo4b3ApCbxVElqOiqDeIz2767EYmkg1VbdivHZNU8D44jzy3ZWIZS7XGwettu3Pr8J4HvXLe+p7LJyZ81JR28+PF6vP3ZZqxsLs5t5yansQwJc6ybnMIv46OfxRQAfvrvD9P7pQbNmDG1w2arpI4h8XlNPnbv4BNYnD8hzT3hhKGkE1xnqMxgGXJg3i+yzhBJIxY19Nus6TpT2jLUrFnXdSxxQLupPnVuEergqCiLaYoPZi6QjWAhapoBeUOt2/wGWYZMaZZNi0YuMUN+WklTsVERk9vQf4SUzjYFIXXH6pADvoOtZoAslKjCmMdNzmAZ+vCLbXjho3X4/fQl6TYEubOJQhiQek+6+8/VMqT2Z/EexY1LXWMClzz0Lh4VNH5ARiB0rR6md7R9d2M6YN/ddKlucjapa8PG5Yno+rqqXOhc6S8MrdqyCz9qTlgQjSoxQxbC5yOXjvNtj9/nLrFoynKYhSwkaVdN7sAu4kbbL5ENALy3chsWrM5kbvSrF6O6norvdOHaGkx54RNPnbgglm2qtZrL7nt9GT5onpv8EsyI42hHXSOefX811gqpztNucor1NJ1oxzJm6CsH9vNtb0Ro549PGI5bzjhA+j6b2ExAn0I+n5YhYwKFAAWLqWbY9t2N2k2pn2UozNqWSMqptXW/VbOHBnHQz1/CL59faPxet17ossmJ/dQdVybF4Dufbcakx+Zjw4664JihRBJPvbdam4JebI+pLQDw6qIN+Mfs1Jpg6uNaBZbFu1G3d+77HzWwCwb37Bj4+yC8MUOpshJPvrtKer7uM1PHjINgd0V3j+SNGTLvbWkZImmkzZ2YaUg5TmsZ6iBbhnTaLnEAuDED4iCvN1iGIrrPJMtQeDVVkyIMBcUMBY0TsXk2vvjZWLNc/NyoenQsN37n0lEjDH34xTb83+PvSZ+5zzVIG6ZLmS5iSgXs57+8s050yZCPUyd53UY9GpE3Bq5mL6xlyOS3XFEWlYOLNce5i5UOdQyJC6i40Xp8zkq8umiDJ+W4e89VacuQ9xq7Gpow6ucvpQvaumMy7SbnAEvW78CTc70Z/FSCLEN+6BYfNeajc5W/m9zCtTXpv2OemKHgNohJKcLWtXBxHHPdqCAahA1dUGpdKWbIQlD9ipBNzc8tTLxc0nGkumMrt+zCfa8vw8+f06deNqGbm3XM+3wrTv/TW542et3kMt/96J8f4Iqp7+OapzKuuW6mMjVjmTsegjTqtkQjkfTYL4tF0adzJS48bM/099m6yencd/NpGTKdKqi5SYNiZ9vuBu3m3r+umP16rArl7vt6bdEGXPXE+1kpH3bUN+Gvb5itLmIfO/OQgQDcDbYqSGeOc6cPU1vO+essPP/hWtz4zMeBMUP1Tcm0i6kJr5LA+0zd2n6m5+0KmQO7VeHUUf1T57V4mOpzaBTGQT4E94Qmm9zxv5uJn/z7QylZiztPqtZuxwm+jzKjMGQuot7OZCEKQy2JydVLRfed1zLk7yZ392tL8ez7q2WBxGAZ2tXQ5LvIZWMZSiZlTZDoerWrIYGjf/0a7mtOdQvIG36dm5nJ5c4k9LRUNrl7zh8d+HtdTRcxq5bLuubNUrBlyH/xk2KGDK5lKqJQ4nGTUzSFWmEoGpE+d1NRB6X+VIWhWlPx1mY3PBcpm1wkJVxe97S3ZlL6eKVfSMKQsODU7NZf313o3MQDOo3lik1yYca0Zai5+6QWodfx6CxzOulM+/wTKPihW6zVDWCQZUh8PpFIRBJu/KwhLqJi3DRfBM0jiaTjKSpti6RsCYgZeHnh+vR4DFtjxabALZB6d2s1xWVFK5MNkUgktNugn3ue2Ea3SOXrmrpL3jUiof3ctI4Fzb/RSCT9W3e+Ffto9m5y3r6a3wQK2VmG5Hk58w5MliE/C0OY9TglDHnd5C5+6F089d5q3P3aUutzqZisOG4fKo9FMWpQl/SxNn0n6Na+2LbLKmYoOCGT+m/vhd1nZVLYuevfbV8diaoyvXCgw+uJkRGGVCVENiSTskCSFLwv/rdgXfpzd1/RUUmuo8v8pxLXeB6lfmver9AyRNKoG3r33x5fWl1qbSFmyHEcK23XFVPf19YZUidT3YZQPCYbK0uTT8wQkFqIp/xvUXpz4ApOr/7oaK2bmShY2eTQt9HQmPBL6zpuSHeM0hRjFdFl7tK5V2T8pP3bEyabnI3VDAB2Cu5qpsnZ9G8gtdkW4xQ+21jrub6OGiWBws56vWa+KSkn4FCfgVqQU0WNoxGFDfFd6OZnR9CmVpVHmz/zHqe6F7haaXfSt6mZ4aLrr7abYN3mSH0PXQJihsQ+pM4vNmuYqJE39YGgBTbpOFLpgDCo1lFHE7AtcuxvZnh+50ddY8JTykBFrYsmWoZcwm4IIpHckof8ecZSKehd927EfmzyHthtcJMzuXP161KFUQO7YHifTtrvGxJJ/LfZbdi1xIvWy7B1hlx0jze/bnL6z4OuYfJsMAlDfu88jKIv6chucOpv12zz9lFbTBnmMpaOjBolmfSuc3IiJLe9wUK0TnHUJLnJOYFChdpvdc/bfVam+cwVyuKxjCXd5t2YkpqUx6PW6af9jkoq85R4ObGQvXvdKlV56wTfR9oypLwvuskRK9T+5QoIjuIoV6+ZHHt0TKXWTiQd7GpIWJv+pWxyjXqN6VbNBsTdUDzz3mo88JbZJG5CHZCmjDXuptY9tjyuNxX/9qVP8ZfXP/O0P9v4BD+CXDSqA1IJqzVdIhG9e8UXzUGzQZvmoM3Qeyu3pf+Wa5uYf1MjusmpwpCVm1wkrS0GgBXNmvawbnI7NRW5gdQCJG6exUkcCF403Qm5rjGB1xZtkNyvggOAnfRYrSqLG6+nbtjcMRkT3ORs0blC2gpT7mItHq9u8oOyyYkCb1PSCb2BFOcj01gPeu5JJ5NdKyzqAlzflLSaA2zT2h5w04s4//7ZvpZP0cqZTOotQzbJP0R0gedBiGNw6rurcOvzn2B9TR2+2Jpy1fO0Sfjb5GK42+AmZxrvsSjwzKQJeGbShMD2ai1DWdYZ0m2C8+smZ8gmF3ANv5ghnUDup8wLIxwnkv6ptXN5NG7/Xrl5F77/j3npmLW0ZSgeTff3FZtrcdN/ZBdRXaKPoDuLRCJay5DqHRE0zNTpVifwuO0zjXn3uZbFoul+YScMyf8W3eTyYcRMqJYhoS+tFpSIJje5pBOcxMZVoIRxk2MCBQIg1eF/NW2R9JnJRUM3OXaqjKc3KDV1jdZStpRNzuA+ohOG3N+6xRvD4okZMtyra1J1N77xaFQbPPv4nJW47YVFaEokjZW6P16zHUfd8RqefX91VnFOLkFayU4BwpDWMqTR5azaapdBJ2iCFYtT2hR6BDIxQy8vXI9/zZPrAnjd5LzPMhpJuVemz9f8d5BLnxpAXttgsAwlktK7FYNhIwjeILrZDG//3yJc/NC7mPzY/My5heciTtDuhkXUpLoLhe5y6uPNxAxl2mCL3jJk91v3mYvzibrJD8omp1pWxM2dzWY8Eomkn6UpO1WQgTmRdDxFeW1R55e6xoSdMGRpGWpKOnhr6Wbfc4qCRlPSwYYab/2XsPsB29TV0m80c9+8z7finL/O0h6v6zdGy5CPO7VINBJBJBJJp+oGzEKJKwxVi8KQRcZH03VVWiO1dtA1TLGcNaYECj6DJZxlyJGUW6pFJBdtvRtTM/nx+Xjho3XpmDUxFsw9/6J1Ozy/F++7MZFEQ1MyUAEUjeiVLX97c5lyXIClziPUm9+BydIhCkNu33bX8g01db7Z2kTc48rjkbxYT5KKdUbsb2IyDfe6amkEx8oyZHaTM82pYRVBhYbCUAvx+JyVePq91dJnJg2qbhDFo5H0hmZHXZO1BkHO6KYXhkzm7lysKz968v10TSTALPi5Ghl38Y1G/f2v6xSNrzipXfrQXKzcsgtXTH1fsnyEJcjHvFOAlr2yLCpppjbtbMAkYTPu4lrFgh5zGE2gOM/6CVk76prQ0JTE5Q/PxbNKymY1hbOun8aiEWlidQPR/dzkZi3bjOc/Wutph47GpNnNyYGdC1ljMom/v7MCAPDp+p3pz/8wfQn+Ne8LTFuwFr95KZMW3F3E3UUuEslk19IW2FO1rOlschHjb0yYanPY4C58oqVOTQwQFDO0WxBsm5JJaXNn2w53Q2DKnhfkJucoG7cwqAvw7saElatsUIyb93jzOR+bnYkN21Jbr7U6hd0P+F1PR6rYtfc3c1ds9aRv1lGvWIBcxU/aMuRxkzO0r/k+Y9EIxg7uBgDYu5feZS6ucZPLJpvcNV/eR6t9bp0ECiHc5IR/vPPZZq3ywK/vhumzU+eskuZctW+I4ybsc3ItQ8s3yvGwsmXI/Htxrfj6PW9jzK0vBypDopGIdo5YsLpGOc73NFZCvfsOTM/bfZbxqOwmt2hdDcbdNh3nGpQPpjpDolCVC+pcqAqYjnJfngQKCFZcmRMo6BWc7c0qBFAYajF0AfTuoFbnPZ1kXRaLpl1danY3htAaC8KQoeiqKYNT2I2CyKxlW6QicmbLkOwOFY/6Z1Spb0xIZuap767C0ubg/XUaH/1sCHKTC7IMxSIRj7ZFh2uRC3qV2RaQ1U3wlc2BnjvrG9OWqSD0liHZTc49xq/P6NKSmxIoNCX83ZxsNuhNCccTHOry439+gO8+KguodQ3NFpbme6mMx9ICju5yahviqjAU4rW54+DKqe/hty8tbj6/5W+bn7n4LNUFqXOAAC8qD5JJeWNkux1379skDAUJJ4mkEzqhgYsqeOxuyK9lyEUtGmzCZPEMq/m1yXYnHd+U1ApQcz/fojnai/sc3XGsCkO2dYZES/gPjx8OwOsO7lKucZOLRyOhBcevHTxAq30WP/vWYXvitObMXyq6xDd+5xIJ2sRKbnLC+1mxeRfeWrrJc7xvwdAQyjGxnAPgfX9q2u3Jj8239qpwXVrVR5KOgYlFfTfB4t6kpq4JNXVNmL3Mv5+mLEPB7QsaZzYp4oNihlzKYplYn4TjpJWL767Ymj5G5ya5fFMtGpqS6TFXnqcECupcqK5DGfe/1P/VGO2kJtmFSqbOkCJ4wdGu6e0tXgigMNSqfPDFtrSpWUS3QMdjkfRicceLi3HPjM88x+jQuaq5g8HdsG8xucnlkJ5axWwZSkoTUSwS8RWG6pqSnk3oJQ+9GypYPYggN7mzxgz0/T4WtROGXMtZYMxQlu9BJzB0rUol4thZ35SO8wlCt7lVEyi4i6qfFcstjDe8TyeM2bNbuh06VDdLkQjsBI3GRNITv+WH6x7n3m9lWWYx170jj2XITaDQ/COT5Ve3cUokHLyxdBOeeX8N/vjqUuM1dbjPfLfPxrkiHksLwjrE95C7ZUj/coKsPgnH/MzCstvCTc5kRfHD5FKsYtpQht3rhBUO6xoT2mt/+MV2q9+7rkquMOQq4FzLoXpq0/P7hjBHuoKR6VFn3OQym7JsNOTRaAQnH9AXALB3b70V6shhvYzjwFQfTrpGlgkU/Gqm6ZRSfn03l4LiqvJRnduf+3Ctx3of1A5VQNTFDOnQWmMC7i0ipGTPBY+bnE/MUND1pAQKCQe9OlV4riNeLuk4mPnpRhz7mxm48IHZaGxKfVkWJoFCiOFhskS591UZ966RQe65GTc5+XPH0Ss48yHktTYUhlqRyY+9h8Nvf9WjddZp18ui0bQbwZzldlo+QHGTc4NjlYXOtNcJO+meMrKfsQ6PSQPbmJSD9WKxiK+LhC4WYOWWXYHZxYIQMyoFpXXdv38XPHTxWOP3kUgElRbCkOsilmvMUJjfuVnFauqatNZKHbrClKqbnLuo+lmGGpvbc9CgrmnBwSgMJfyDOK3c5HwsQzrce3A386l3aN7Iqc9XLbpqEk50C15T0sHidbKrh00Bv9RvvZYhlbK4v4Auxo0lHXkzalNbCxCEIYNA87tXPtV+7uI4TmhLjQmbmKHahvCutCaXYhXT3BnWbz6sMFTflEyPs2xoaEri0r/PTY+BjDDUbBmyGHe/P/sgDBVc4vwUCkCmQLgY15ZNfEEsEsE1X94XvzlrFB6//FD9MdGIUdCysQyZU2sHxahk/lb7Za0mo2a+LEO634rjUzdHzRUsGv7nSt2UeutiQgC/p6LNChewCd+0wxuHpyPI3c7GMuTOv0GWMtGik3Ac9OiUmS83N88Xcqpr4JFm9+1Zy7ZkYoby5CanYqo15ionKxTlgOMEKxszbnKqS55+Xm2HslA4YWjKlCkYO3Ysqqur0bt3b5xxxhlYvHix72+OOeYYRJqDK8X/TjnllPQxF110kef7k046Kbs7ageow1C3AMZjEXTtYLcpMZFxk0v9OyjDVNjg3bJYxKgBMLrJKe5QqYKP5m5Y3+i1DAHAuX/T++faImaIs6lxMah7B+N30Yidz7ubZjooLiCjgQs8pYRu0XQF6t0NCXthSOPyE4lEpAQKarYpXTdwJ+FYNJquS2N0k0vm7iaXsgyFEYaaY4aaXMtQLLOR07j4qO1T3eR2GVyltJahZBIrNmc0xI7jhHCTa7YMGa6XalvUylrpEolE8NwPjsC/v3eY9bzj3ldY1y6XXNzkVOoag7PJZRNXaC0MGcZ02DEc1lJmsgzZ0pBISslK3KQGu9KW3+Bzq2ncXcHGNGTdcSOuRyZXSz+i0QiqymP4+uiB6FVdIX13+F490KNjOcYP7W4UaKosFCdZC0OSZUh+hro5sCUtQ+K8JGYidVmwxs6K6LZDvfdM3Rz/hABiHKdL0K0ts1yz/OZCQBcz5O3XaaEhYH2OxzLeLKoCa932OjiOI7Un6cjzXCaBQssIQ+qc6u7FGg2WIcdxAl2aTTFDScfBLo1w3x7d5Ox3DgBmzpyJSZMmYezYsWhqasLPfvYznHDCCVi4cCE6duyo/c1TTz2FhobMgrJ582aMGjUKZ511lnTcSSedhAcffDD974oKeXJrb4Tx4tKZZeOxCLp18A+CDiJtGUq6Wj//84V1z/KroGwyNTclZFeVWDSCMl83Ob3G1yY42I+OFfG0FkfVlOjwM2dHA1z9XGp2N+GFj9YGWvrc++1QFjPGIujQCQzuO6+tb9Km/tWh0/TEImrAfrMLZnOfqSyLeYQBVxMVi2YmR5Mw1JgwT8iRSMTKglDXmPAEh/qxO20ZSv2/Ih71jf9R2xdVLEOmDV08FgGU0JOEA8ltsSkZnN7UxV2sN/hoTctjUVSGeBYAcMCALqGOd8eEyU0uiGQ+3eQaghMoqJkNbbDdhxqrsIe8XtiEEnVNCc9m+acn7ePJZGr8vdJn3WQxdelscsHnUDc+GYWCHncDKGaeG9CtymrN7FCemWf8NpL/uGw8mpKOb5C6zVxhmvaDY4Yyf3ssQ5r51T1mfU0dPl2/A0fs3TMtVOYi7CYSTqCg8MnaGt/vXTL7A8VNTtjch90DZ5M9UUfQOmmTIj4dPxfQpnhUSK2t1Ddbu303Hnx7OZ6an0melVTST4vCo60wZFMI20XNCFzfJAt5HssQcssmp7PKFb0wNG3aNOnfDz30EHr37o158+bhqKOO0v6me/fu0r+nTp2KDh06eIShiooK9O3bN0xzigZtAoVoFN0sNLTi4mA6rzsOgyxDYRMolAmbR1sak0lJm+LnxgDYp8wNi2hBCEqQAPgvftFIaoIMYndjAt//x/zA49IxXuXhhCHd63MD6Xc1JKzfr64/RSP6mCF34aiIRz2/S2sSI5l3vMPHncH1pdZhY0HYUdcUShjSucm53Vnn4qNqAdNFV5vvzbTpMFmGROF0xuKNePuzzVbtdpUbn230alpdgtzk8kFQrFQQahpgl1g0EnrM28QMqQWA84lJ+RM6gULomKGkR4nVv2slenYqx6adwVYt1WXLtZi7Y9nGdVO9R3cTbxLuRcXS/BuOR11jIjD7IQA8ePFYfF9IguKnoIpEIukNnOkd2MwVWafWNtQZAvRucu5ceexvZmBXQwIPXzIORw3vJX2XDU1JJ9DqZqvMMHkBuElGqivLQvf3fMUp7wpyk7OIGXLn78aAMVgmFV2V38+abbslQQhwFV1CW5uF4cp4rFWEBnfdd+eoCqWml02dIVdxoVrNEoZY33YoC+UWM7R9e8q8qgo8ftx///04++yzPZakGTNmoHfv3hgxYgS+973vYfNm88agvr4eNTU10n/tCdVEq02tbekm19WnnohqGeoeEAvgF5CtozymrxHkh2oZCnIxM7nJ5YroJqerE6TiFxAYifjHPYVlY7PG3yYOSUSnGU9bhhqarAtc7tL5AEfVbHJyam1dWxsEN7lIgGUI8N9U2wpDYdbWOsUylEqg0OziozneHDPULAyZLEOavtOUkONlLn94ruSu5Ie7IPkKQ7FoKMEwG9z7enTWyoAj9SQNbnJBCU106IQh9bHXZFng1QaT5TK8MJSFm5yynlTEY4EZMl1UK4U7jt052iZduaoHcm/ZNG+Lc2X3juXo37Uq8BrDenfCsSN6S+e0LU1kjhnKPoFCYF0bX2FIYxlqPt6dY2cty+x/EoryMAxJxwm9rptoSscMyW1w15XOlWWhN8H5ihkMigdU+6JuA59e0ywyq2WEIdk992mlTAWQ2t+JezxXCda3S2WLuMmp7GpI4O9vr8Cn61O1n3RrdZAiyf1NQyKZlYKkPZC1MJRMJnHllVdiwoQJOOCAA6x+M2fOHCxYsACXXXaZ9PlJJ52Ehx9+GNOnT8evfvUrzJw5E1/+8peRSOgH8ZQpU9ClS5f0f4MGDcr2NgqCKl1rs8lFo1Zucn4CUzpmqPn0nSrivhuksH7bZbFIYDYUNRhbLKIai6biw/ysKv9bsFZKWZkvxKxjnSwykPlpAmPRYDc5m2Bdl589/REAb3E0APjSPr2Nv0tohGrXGrirPmEtDJmKroqL6u7GhJSFSjfBim5y7v5np0/chkngicBu0dxR1xio1RNJxwylhaGY70ZO3Rh6EiiEsgw5WWdEdIXVZRvN/vTxqF1Sj1xwF7yPVtvFHKgkHEe7+bfdyIvUa4QhdfzY9v9sMPbP0DFDWSRQUNaT8ngEZXFLYaheLwy54zqbjU9aoWD4aTYbJZ2SwjYTl9FNzmLeN1qGAgR28d7VzbXO8p5IyCmKRa8Q8fd79dKHI5hoSga7yVmfK6G3DNXsTrW7S1VZ6EQY+RLUwsYM6dzz0t4OFtnk0m5yimXoA005iYampDQ/uBmFB3StsurDuXrG3DPjM9z0n4/TJVUq494ECkHXEPeNdqnOs2hogclaGJo0aRIWLFiAqVOnWv/m/vvvx8iRIzFu3Djp87PPPhunnXYaRo4ciTPOOAPPPfcc3n33XcyYMUN7nmuvvRbbt29P/7dq1apsb6MgiANj08769KZM3ASkYoaCLUN+qYQbFMtQPBpBz07mWCyTu50Jm6Jhe/SQEw80Cult3d/6CRJPzv3C+F0udAxrGfKZtBwnuHBrZx8LnokqjQDl146b/7vQeN3aenvLkI6kIy84jpPSErmTqGp6B8TCupnFw8/tz2+S9Ut36roC7qhrCpWGVbUMVZXFfNMCq+un23/dDYBp/OiE/aakEzoLmPvq3ayEKzabhaFIJGLlepQLuWo1TZahcsuNvIjOMqSeJ5fCzEGY+p1thkCX0DFDmgQKZbGoVVIYwKuYc9NQuxtfK8uQ6ibX/H/TBsvGpVglfQnhlLb9zzRn2liGzDFD/vewfFMtzrr3bSxYvd0uZshxpJTb4nVFT5J7zx8d2GbpvMlkHi1DKWu2WprDXVe6VJWF3gTnq21B7uRqV9T1zYwwFGAZEmojJh1Hq4QUaWiSLUNrtqUsQ/27VllZN3Op/wgAMz/dKP27QlESJZ3gBEWiMGTzzkrGMjR58mQ899xzeO211zBwoH8NFpfa2lpMnToVl156aeCxQ4cORc+ePbF06VLt9xUVFejcubP0X3tC7Nxjbn0Fj8z6HACkegjxaATdLFLc+i16rpAlbkp7djKfM6wGyUYY+urBA7CHkIktIdQ9cLUirWEqVhHjhGxq0/i1Mek4gfeQzcZUp9m3SdQg4lqGdtQ3ha5uLzJn+RaPBaCuIVMzSp1ggcwGMR41Zx2UjvdxEdq805wswLWO1tQ1hlo4XCHI3SR3rIinFyfd2uBJoODGDLmWIVNqbYNlKGwWNreexY66JjQmkoG+/l1zTMASRM7CkKPf/Ntu5EV2N3jdaaORCAYILliFcJMLu5HJzk1Ovu94NJqVdQ3wusnZxKuo3cAdF6aELVnIQmnELI+2VghTN9V5SainNBZdtbj2uyu24vKH53qeoc5N7uWF63HSXW+k/71DENzdeftP5x4ipTC3ockigYItiaSD0+5+0zPv1KSFoXjoTXC+POCD7nH5plq8INRT0q2Fq7bsxul3v4m1mlqQLtFIs3Iv7SYXXLusXii0CmTWCVs3ufqmZE4xOF5XWHUABt+DmPlO50avkk2q/EITalpyHAeTJ0/G008/jVdffRVDhgyx/u0///lP1NfX4/zzzw889osvvsDmzZvRr1+/MM1rN5g6nmgJiETsssmN9MkA5XZadxMXZBkKHTNkkUChujKOGT8+Bt8/Zi8Aqc2Be//uxj7IqtISyMJQbgkUko4TGOcQlLxCh85NLhYyniIog6BI2BiTuqaEkK7T+w7TbnIBVgr32b348Xrt95trG3wthO442VHXFMoH3RWGNjcHmvfsVJG2DNkkUHD7r9s3wsQMJZJO6GKCbvrgmrpGfPjFtsDjW1oYylWHkXD0zyArYUgjFADAqz8+Gvv2SynLCpFAoSGkAiK0m1xj0iNwhXGTU3H7qutGlFTmah3qxidoH5SNZcglm82zae7WWd5zdb1T2bSzXhMjHHwTosDkWjGyUT4kkvmMGXKwaN0Oz+fpmKGqstDZE/PFah8BxkVMXmSyWn7wxXb89mVzfTR3bnKXYTWbnI6GpqQnOVDPTuWoLItZ9bdcLUPqmFFTa9fsbvJ1uQZSfc/1/rAJpyh6N7lJkybh0UcfxWOPPYbq6mqsW7cO69atw+7dmY544YUX4tprr/X89v7778cZZ5yBHj16SJ/v3LkTV199NWbNmoUVK1Zg+vTpOP3007H33nvjxBNPzPK22jamuAbVEqDWb9AxpGdHPDtpgva7zzbW4u2lm5BwfX2jEfSsNgtDuiw3fpQFFEwF3BozkbTA05TITB6udiWstSMfiAuhjbtEkDAUtMD36VJp37hmdO5Ctou1SxghLGz2sZSLjjmBgmSRrDZbJHOxWAEZy9BHq7drF2sTbnHZzbUpq1PPTuW+aYE9AfpKAgVdfSZA7juuxr4pmTQKbiY3sX5dUlaOtdvrcOY972iPue2rI/HIpSk3ZBs321zIZlP7jTEZT4KkIWYomwQKaiAzkNqUV8RjaWu4G9vQEpg26Tpr54n79zGeJ2zcZn1TwpMZqywWRXmWCV3KYoqbXPMz9RNQ1akxaIrKRfeVzUxhUtjpPhc/O3JYT+M5bdesqrKYVXpylUdmfZ5OpKMqD8PQlE9hSHMjjuOklQzZxAwVimxTeqeFIdcylAi2qqhucgDSSmkbj4lchSEVda1+XrCYiYhW9aqyWPp3uxtsYobaRz8QCTUt3XPPPdi+fTuOOeYY9OvXL/3fE088kT5m5cqVWLtWfriLFy/Gm2++qXWRi8Vi+PDDD3Haaadh+PDhuPTSSzF69Gi88cYb7b7WkAmTFlGV2P0WoHPG7YHTRvXHmaMH+go45/5tNhY3ZxHJt2VoaM9OgZ3e3byXCRrHhDK5F8JNThQSbCwifkJI0gleqPbqGS7wFdBvCsMuiOWxqMYsridswP1uIZOVbgPfKLjJ9fLpd7niWkBss7G5uK4Vm5pd8Hp0Kk8v5ltqGzDh9lfxvhAQ60mg0PwqgmKGxP7t1niob0oaa9j07awXnAd282bdEt9t947lOHf8HjhyWColb65Fm4OwWchVfnbyvhg3OJV9NJnMpNYW+3V53L8fHjuil+ezJm2K19Q53X7dkgkUTOgE/bPH7YEhhvlgW8haSHWNSc/GriwWzSruCsj01bRlqLnP+53PlEDBfI1sYobMFtsgTMK1Lk5CbPrDl4zzfO9iu2ZVlce0BT6DqG9K4qIH5wAQYn6b7+OW0/e3KgcBNGeTy5ObnJuNTKQhkZRihtrLHjjbpATuO3D78LSP1+H+N5f7/qY+kfTs+Vwri407a31jMm/uhOK1gxjUPbPeVJbF0r+zcZNrj5ahUL47NhORLunBiBEjjL+tqqrCiy++GKYZ7QK/Z2WS9NVNq9+Ee/6he2D//ikXuaAN8pLmys+xSAS9fQSn3Rad3OXaL++D4/btjXtnfuZ7XDpJQvOgb9RYhsJqgr8xZmDWiRUeuGgMulSVS5tcGzc5v/U7mXQCLWRhfb2B1IT74xOG4zcvfSp8Fu5ZRSMRdCyPo64xuOaIrZucWwcmtREzay1dy0c0QAjPlWwtIFo3OeE2Vm/bjV8+vxCdKuL40QkjPNXbY8192r31XX5FV5upLIthR12Tb7KSvp0rsXLLLs/nOmGoc2UZ6hrrtd/7pd3PB9lo+MtiUYwe3A1zVmxBIplxC6sqj6XjJIKsGt85ei+8tlgOCtbVu3DfpSsMtaSbnAndXF8RixrdiTYZYuOqK+LaGl0rNtfilU9kJUCYBAoq7lwczjIU1k0u/E7J/UU2e1iTG7bOJVFsu5+Vw3Ye7lAez7pO0MdrarB5Zz0WrE6VDnEtsRccNhj79uuMr9+rtw6LNCWC6wzZ8pnGlaq+SRaGtmZR2Dgse/XqqG2LDXWNCVSWxbJ+J65AIHapLbX+a2tDU9Jj0nTHk40Ccmd9U17Li+jie4OQLEM2bnLtUBpq/WCNEqChKYkPfdLNmsahOjD8JlzRRUVdXNRNbXl6AEd9Y4zCWIa+c/ReiESCA+NjisDTlNBZhsJ1w4P36BbqeJExg7tj9J7dJBclG02Jn0uQjZvc0JApUVPXjGDyl4ZJn4UVhuKxiFUKWUDvQ6/D3WTvbsi46Oja5W4EY5GWFYZs3EkBr7JhV9oylFrMenSs8Gzs3l2xFa8t3oiv/PFNr+DvpogPdJPLXNdtg1+RQJNLZc9OFZ6+Ko51VRjq1rGFhaEs1MCxaCQtPIpucuJ9BG3kdVYKvWUoRVXzM9+0w5yEIyy241AnDJXFo8aU25sNG6srjx+u/fwfs701nspzEIbceczNdOgatvwEVHXqC7IMtfZGySR86Swmg7p10Bxpf06VlJtc9hvZC+6fk/5b7HO2/S+RdEJniQ1DXWMinUChcxbZ5LLhu0fvlVUMLpCq4Zcqa5Ddtd2aWGHdwFTLkKsgs1lzt+5qyKtlyNZTRLRqV5XHfGOGVEtl0bvJETsu/fu7Hi2yDRP3TfmSuz7ufpsNMTha1XypE4UriMRjEezX35x5ryUmzXSShOb/NyadtLuRO2DCagrF57Jvv85Stjrb9oixCjZ+zn5NTCSD604M7dUprXUU4yb80C142VqGbLC1DHVp7nvn/HUWdjZv6nWbr0ZBUBJjhrJdyEzYJBoBvC4JuxoSSCYdbBFihsI83XU1qWxZbv+xSaDgVvL2UzyYMj52rop7EmJUCe92oLKRsxUSsyUb99ZoJFObLCUMpTYJYh8N2siXaRQPiYTjcWN0WzdyYFcAwLJN2WmTdZji61Qrt8764LdR0FmGvnrwAFwyYTD+M3kCfnyCXigSicciWbvJufNYQ1OqjljCxw3WxZRa23iNVhaGTP3piL29MUH3XTAaRw/vhX999zD/k1reQofyjBUibEwmACxcmykoL64xtvF6763aKmWmA7wb11zYWtuYVu62lptcPBYxPv6vHjzA97fra+qyjhcCMsJyrq79bp+06RPbdjVapbi3pSLADdlFVRhX+FiGvnrwADx++aHpf7dDwxCFoXxTW9+EN5Zsyuq3g3t2xKxrj8PrPzkWgFufRT7m4gmD8fdLxqGPEFegLsDqwtWYyAgffhuNrHyLA8aoqwWMpQNzk/jpvz5MfZZ2oQu5wZc0ZPqJyVTkNK35DBmU6CcwJR0n0FWrU0Ucj146Ho9eOh53fH1UOsOVH7pNQ2jBMSpvjMYN6W481jb9ty7+R9eutGVIcZPLd/2bHpZWp7JYFBcdPjj9710NTdi2O7OYd+tYHkqj9cXWVOKYMKm105Yhn7FWFotqY0o6V5ahc5W8kREFWDHg1T1eZe/e4d01TWSzIXALLQPNwlBjxk3OxS8T2tHDe2mz5DUJKftd3Fd51uiBed0AAmb3FnV+1SXJ8Htsuj3PaQf1RyQSwYEDu+KwvXp4D9C0oUy4yOVHDgn8jYs7P85atgVDrn0Bby3dnD6nCa+bXIBlqJW1xqb15bh9e+PhS8bh9IP6pz8b2qsT/n7JOIwZbJ4nAfusdnM/34qP16QEGluNvIu6URbHW9Ca+dOT9gGQWvvd0h179uiAP5xzMD66+YRQ7fDDTfJQHo82F61u+Xcb9fFICfLyWL1td06WOjeOJldhKEy8dGqNyqcwZNcPxbkrEokIMUPetatjRVzah9IyRPDyQn16YBvK41H07VIpFQFVNUCHDu2Bo4fLAcTqgFJ/41pB3AE48+pjcMsZB3iun41lyAmQhtxruovzmm116YQOW5uLt4Xf4Gf+jka8AiNgjgNyrxUmBbP3+vIFk46DK44blg4MNzFh7544ojlDkY0Xi94yFG7IxqMRHLJHN0QiwCUThvhWMLctDKtz+dP55YvCkCgs9ssis54ffS3PF49FcPNp++PXXz8QQKq/uylsK8tSrkVh5vCvHZKy8LkTv8n1TbRkuklS/FIoRyLAi1ce5fm8c1WZxzIUAXDaqP4Y2K0KXztE1oqKdcq+OWYQjhzWE8ft29vnjsKRzYIXjQiZmJKZuUm0DJmCig8d2h1/v2ScoW5T0hMHEBESKHTOszWyqlzfRnUu0yldohGzZttF3FiI/cfGIlAei0qb0h8cN8znaBnTJjuf2eSyihnKYW+lsyR2LE9t3I8a3suYsMQP095U1zdfby56GdYy1LuzrOQp83GNF6muiGPfftWezy84dE+cNqp/XgWWDTtS1nHXCt0am+B4NGr0mgmyKj/7/pqs44UAf8tQmG4dxo11W22+3eQsLUPK3JXJJqdzk4tJAmo7lIUoDOWb/l29Qc626DYB6jyuSzagTvbqQHWLpLmddc8eHXHBoXum3fJcVGHIxtUiaJCmXeGa722xkJHGNd/bbvCH9+mEO78xSppwU8KQ95mY5jv3Gbj37pdQwoTq5pVIOujWsRxPfvcwVFtqoG3u2V3wftQcL3DbV0eGDlqPRiK46dT98P6NJ+DGU/fznYRtLTY6q4XeMpSxSMaiETz1/cPxf8cNw89P39+y9Xb0sChOnGpj6t5dQXl3Q6Y2jTuGbCbxI/buiek/OjqtlHBfpakKuppAIYhoRO/m1LmyzNO/Eo6D3599EF6/+liPoFQWi+LNnx6LmVcfg199/UA8cul4a5dJG0xaTT/BI9LcF4CUQsIdp6JlqDyuP29mvvB+r4sZEt9ltnV3TJjd5OTr6OYh0TpmokfHzLwUxiIAAGXK89MJA4C+DpVpk+33/NR7aXMxQ5pnJrqQZtMekxLQz7W9MmQdN8+5LWOGotGIVmgOmy3UBtcy5I751nizfuMnSMh4ddEGbM8hycOgZpd83XsOU9MvjDC0ZVdw8qMwVPhYKMV1R1UYu5YhXQmWfl2qpGdCyxDBuCHdJVecMOg2QOqkpttEq+506oKmWoZc/nTewfjP5AmY2KwtfuUT2aplk/YxSGHhLkRlscwGSMWUTW6P7h2kNt997iH42iEDPYuCbmEIynw4fmgPPPeDI/DyVUcH3IEXVWgQNzyd8qyBBlKa3bnXT8S54/cIbRlyFw538ffTLKsuWCaG9PS6WmmD2oXU2gBwyB7dcNXxw9NZEPOF7SKvBq3WNjR50tbaTOJV5THsJWQHDPqN2IdtXGVMLhGdq+Ke55xMOr6JTAZ264A9e2SE12wD63WYNmRXnzgCv/zqAXjrmi/h3987zGMJdB+XGIjbsSI4gYKbtUpvGdIIQ8Lffpr0rx08AI9dNh43fmU/4zEqtsKQDpt9QndBwBf7l+78qnKiTMlWZ5pfdUoEU+a1ihCWoSDZorVjhnT3JFrBs2mOWdlm/o2tZeibYwYBAFZvlQuJikKdXz8zrYnZxCwdM6IX9unrtTK5uMJQrpYhm72GS1wTPuAS5KkCZNLXZ9NUdy7TzbdhYmHDhAZsDchWFxa1hIuIOM5V7wV3nf3dK96itHv17iT1OQpDBEB2RQMBvS+nOqmVGWYBcZOr/sbt1OrnFfEYDhzY1Tix2txHkNCRSZLgP3m7iJu97xw9VLvpFDUQMYNlSBdwqGqsDxjQJasgc1VoEJ+BbWxCvUXmPvEe3JibbGKGRESt8djB3aTvbJ+FLmGFrg81CMV+/bjzG6M8Vsow2KRGBzLPooNg7nctQ66QaTOJq1pB9TfXn7Iv7j1/tOe6gF1a04ShCG1VWcwzJsMG1oq/11kGwmAShqory3De+D0xoGsVRu/Z3VPvyH1+tUIqf1GgNW2M0sKQ5h01NCUx7/Ot0meRACHC5fC9e+LwvXvikiOG4Oen2VktTQK4zSYnFg12k+shJNGQLEOaZ37e+D0k1+l4NCJJgrFoBP+74kj8/uyDpGyiulg70/oSLoGC/91lE2+Rm5uc98eyMBT+5CaFhZ9lyFYY+fLIvgDgceeytgxF9MKQbYIcke8evRdu8FESbNwpC0PZvifbjKeAm5EyvGXIjSPe0Zxi32Qx9cON1da95zCxsOEsQ/lLVx6LRnz3daLVSC0Y7RdrNLRXR+mdtENZiMJQS5B9jYdgYcg0CcqZZuRj3Hnb/FuD/3s+LEMWSRIkzbkw4MpjUe0CIG6uo1G9Nk4NpgaQ04ZbpIPiaiQujLaWIZMJWkQX6BnWpcMrTGeus3fvatx0amahs53Mh/XuJLU3GglIoBAwM37tkIH427fG4GsBmYB0/O3CMdZCXJniJrdLSA3utt9mElefqXrrXTuUyzEfojBk4a5l8mmPaBKghC1OLl7/vvNH4/C9euDRS8eHO0kzpveqbpzVxdddNN2UvB3KY5IAZHLJSrvJaeaS6Ys2SJm3gtpk+s52eJk2ljYa7mgkEtjPxBg78ZS6NSIaiUhzUCQSkQSSSCSCfft1xukHDZCUNbqshTbrS9Bvgu4tK2EoBwcs3Tp2qJBIJqsYmgA3bB2iK+iRw3piRJ9qbXILk9AkzrF+7yMakRUNLtm46ZXF9IKVy9rtcsyQ7lEeOcybtU/Fz3335lP3w+AeGQVcytvBe9zXRw/Enj28irqqshgeunhset5363XFohH87cIxoRSM7jl0c1AYy1AYhbmb7TQMRw7riUOHemOY4wEuumKmOVOhWB2dK8sk92ZahgiA7IUh3YLtSY5gElwstEamz43aQBthKEAaUusM6RDvSdIQx6PSpO9uviTLUDQi/XtYc7asE/bvm/6sU0Uc44Z099VwhUHNVCfOGbaWITVX/+yfHec5RicM5ZKGHJD7ZjQiP3vbBArRaESqzm7q72k3OcuJ/7ffGIWZVx9jdazLxP3sBVydm1zGMmQvDKkbHnXi71Aekz4TraI22lld6te/XjgGgHeO0An9fohtH96nGo9dfmg6qUdYxHOJQejqvKH2Wfd3Nc3CTceKuHSuoHknm/pGfuNGvJ6tssFUH8Smr9tsFESrnclNLhpJzTenHdTfY6kwXUK0aotxSQDwh3MONq4vft1MvVagMGRx/x3LY7ijOdFJrojvZOK+vXHV8cMx6Ut7h2qPynCD65if4CBuNPfu3Qkv/vAo/OiEEdIxQ3t2NL4DMaY3yNNCNy9k4yYXi0Z9x86iZgVEZx83OZvSFx19LEMdyuX5IW6wDF05cZh2P/KVA/vhmBG902PWVarEoxFM3K8PPrnlJFx/yr6BbRTRWoZCeJnYpkYHUunLw/LIpeNx+F7eeT1IEeEXM9Rk8Fj4yoH9AChzUzuULNphk9s+Wdd40HRU9TNjgKvQEU0DzTTpmwaIXQIF/81YOn22pZucuMmoiMuWIfcUqm+qqOl47PJDcdtXR0ruLueN3wNPfucwKbtWLqiWIfEZ2FpXVH9cnUCh0/qH1aqqGqy4YrEQBeEwGbdE7b2pn4gJFGyIRCJSrEQYbBJh9OuSSm7iCiS7GxKemCEbDbS631U30FXlMSX9e+Zvte/o0C06xzcLfaqgENZNTry/XJMKxA3jVu0P6ubO/ZlrGaquiEvnEhUnPzlJ3iwC9mNASqDgI2Blo9E0uslZ7AJSXmz+1xG1zKYECvd/ayzmXHccenaqsE4XLM5PoiveKQf2w2mj+huVVk0+Jkj1meUjgcKHN5+IbzTHzgD5yya3f/8u+L/jhkmCSTYxQwO6VuGF/zvS87mvm5wwRlzLn9iPqivj+N+VR2rfQc9O5VIWzyA3uaOH98IZQspwIDthKB6N+HqIuAqNtGVIc4w49g4a1DX9tziX+c2L8VjEowDVPebyeFRrsHOflXv/rpucuzaWxaK4ZMIQPHLpOM2v9eiev6k+nI4wMUOqhcYW3bocdFXR+qNOKWpB6MqyKN74ybG48xsHea5HyxABkH3MkG6R8FqG9OdWN1+i5j7ot6bJzipmKOB7teiq3zGAHNxXHo96JkHx/+7f4u97VVfg3PF7yHEkeRqXZx4yEP26VOIMxZ1L3JD6abhEVMuQKV2wSmhhSJmUJC244nYVRrMlnsekyW9I6GPV/MjWqvr4tw/1/b5DeQy3nLF/89+pvtGUdLC7QU7yYNNUr2VIuVZZTEmHLAgNFhuSRoMGDvA+ny/tEy5VthhgHCZoWYf4HCp8hGN17Lv9oaZ5U9KxIi5niBSOjyDicc+wtY5aC0OxzDuxtRLYFl3VYbNREDNTSZYhYWMfiWT6srpxMV1BHONizJDbF0xj1S8dsbfOkPFQa3Kt4yKiKoBUss1upytg7neuDkKf0cXrVZbFUBGPeQTqE/fvgzd/+iVJgPPrZ7FmAeausw/GMSMysWQma6Yf8VjEarylEygE7GHE/icmk/HzqIjHolIfMyWIMBUTddvktQzJFuEjh/VCn8522WV1Y7hvZ/tMwmHm3mzLgJhcav3wc4XTuesN6t4hPd/nup4Umvbd+jZKths63UIcVEPIxdV2ACkT/FHDe+HE/WUXItMCYxoApmvdfe7B6b+DFNOuUCIKXG7sjqvtlopSihrmWEwWfFw3OeWzoMUsX1qK335jFN766Zc8Ao+UTa7CTqCoUyY4fRII7+/Cusn5pWaPROSNQjif52DLkEuYjU22m6C9enXCgxePNX4/9duHeixDQGZDHs9jAoWUW4dwvGQZskig4FMhXXzuA7tV4YcThweez3yu3MaFVD+pLIxlKPU7N+V/p4q4MUlAJAJPHIC1ZUi0gvncq9he26kil2xyJs22iI1lSMRUcFZFtAz1FKyw6XpwJjc5X2FI/Xfb0grLxSC93+ezIK+tZUhNKgIAdc1ucN4i6jGPJdJvDIjf9anOuK9maxkSz2daI9x+pWuW+FmVIACJ1iC/ebE8Jq/xZYpw5FIRj2o3JO47ca+xsz7jJqfiV3PqsKGZgsday1B1C1mGshSGtN4SAZc1CZQ6VA8G0dMgl8K2hYLCUAuQrTCkkz1sEyi4GwsA6aB4T1puw0Rtqmqua0//LpX4yoEZ83tQKks3oYA4+L98QF+8+dNjcc95h3iOFyfLco+bnKu9lz8L2hvlc2mORiMec5g4Se7d25t2+g/nHOz5TJ0sdPeg24CEFRbUPiBuTGOKZag8HrVeMMUFuywW9e0HYXzyc0m7e8zwXrju5H0N9VOEAP1YNN3+tMtEiJghb8C4/O+qcsUyJDwrG2Go0WchEbMBXnT44Ky0vS65Fl+U3Ft9ssF5YoaU63ZU3OTE9PHRCPDn8w7B/v074y8XjA7VbvEwP1cfU7ILP0zPPZvU2qrw6BYA1rXJKAypMUOGWU+KGRIsQ+5GxjT+/CxD6vtoY7KQxwKg8s2xqYLEYeNGdPj1H1Gg6aqxwu9u9hZQ+6ouptfPHVM8XLR0ZDNXqDFDJvfQTB/2tlXsH+I8IbZnsKZ2nUs8GpWSiJTH9cWxy2Mh3eR078rQeW/4yn74s7Bf0f02THY6eT3yHzBh3eR6NQtBp4zsh4cuHou3r/lS+rugoemn2PzF6QdI/UmdE8R5n8IQAZC9xlW3afQuTsGdzJ1M1YXTNFEfZ3C10Wlf1Kv7KLEBZLLEiBNFdWUcA7t1SLdTXMhVDbO0odG5yUUiuObLqUXsO0cN1bYh34uz+Az+cM7B+ObYjG/7N8YMxKmjMsLiLWccgNNGyb7bOvSFJFvYTU4RJMuiUd+CbCKqEOUn8IRps99GN6hGTyQSweVHDcWRw3p5vlPHpKuVrNndrCV0Y4YsOou6oVL3vx3KFYumxWZCxC8+Q3x/rV2vRUW+r6j2b0DnJiefp7pSDpAW+1IEEezduxrP/9+RUlIUG8Sr+rlwiBsA275qtKZbptYWmXbFkVKtoI7lcWMBQ9OGS7Uim7qx6D4sxgy5TTJtsnVzkfrb9LVboPRmLmeMx/TP0qWyLIZHLh2Py47Urx9hsK0zpFPYpAtA+8R5ugTFDLl0ESxQ+YgZMp0jnelV0yzRglAlWIPEuXDv3p3w+7MPwm/PGuX5fZmyvpTH9ZahaDSi9VRxj3Wv7cY56Z7r+eP3AOAtO3HpEUOkmGPd81c/G9qrI04/SL/2i3OOaI159NLxGDVQrsNnK1hcdfxwnH5Qfzx+ecplPBqN4JgRvdG/a8Z9L2h983OTO2BAF7xzjTfRk4s4xzZmGedUSCgMtQBZu8np/JmVzhtG4PYWbNUPhHgsirev+RKenTQBM358TPpz3cBRJxu/5ojuL+LEo8amiONGihmKRaWFNZoWhjLHx6IRHDSoKxbdchKuPVmv2cv34iy67Zw2qr+iuY3i1tMPCH1O3bNu6QQK6iXL4lHr7GTiZF4ei+KiCUMwoKveZzpf/v+2mjfd5dQx6VpofvnCJwBCWoaUg9Rx1qE8Jr1POZtcsEuO3+InJUopsI+20U0uJm+Y1E2H2tc7VsSMaYPzpcjwE1IqJDc5W2FIvym0SZ2uJn0Z2qsTfnRCxt2xQ4VZmBaFRrGX2LrJiZZJseiq61lgek6mTFKALoGC8dCCUKZYw1sSfze5TDvE1OnuJtLV6KtzVdhxLsXoVOqFD1vUmKEgYUi/jmUWMvH3Yl+MADj9oAGSItGlLCqPl/JYFL89a5S1e6P7+Fyvk511Zje5r48eiEcuHYe/XDDG/5w6xbUyb736o2MkLxrpWOHah+zZLf3ZEcN6hordFTl+vz74/dkHa71TxHb5cfAeXdN/H9scbyYm4vALSRC/87Mkt1Xy5yxL0mTvJhc8UZuKvbmIWllT4LKO/l2r0hqEBy8aix6dynHjsx97jlPdofyyyYmTlajtUv2OxYVcnFBUy5A7AemCrf0m+nwvzgO7dcDUbx8qLWgiYfyBAeD2r43Ufq6LHclnau1YRNaklcUiaa2ZiUHdqzznKYulssC9+dNjMeTaF7xtyNMLGNanE+av3BZ4nE5rqL6Tnp0q0jUyADGBQnjNvvpOqspjcr8NGTPkl0BBFEJzjfnJFbFQom/MUIC7bqeKMnlMi5ahHDavtkVXs9ksmyyoHcrjeOCiMVi7vQ7XPb3A0C6vpUPsQx3L5RgqmzYFrQsu4mZUfGe7G1wXLf219u7dCYvW7dB+p65bubpfasnhnGoMWkvit4bHFO8Il3997zDc/r9F+FmzMk+dT0ylL4xtEG5SrlcV/uZjirVlRN9qLF7v7Qd+liHRoiIKhOJc6La5PB7F3OsnYuOOenz5928AaLYMCSeuiEcxalBXfHDTCfjhE+/jPx+sSX+n24+478RVRPm5yUUiEa1ngfec3s/E87nNMHkziALub88ahbtfXYJzmq1S2TK4h9nV0CWoB1x+1FBEoxEcNawX9uzRATMWb8Rx+4ZL0gP4K0/aKrQMtQDZCkM2G92gDi9mIbJ1k1M5dp/eOHBgV+3CESaTr1iAVNwQqemnxYXcr0ClNpuczS21wAp46NAeGGFTa8LigZ09Tj8J6uaTsMHJfgkU1HPZWF7cAp3SRjxi1grqrpMNkQjwx3MP8aSLtb2eOiZVK1YmgUJwW9Tzi9a3eDSCciXA15SCGvAmBwD8XZJsUuj7cdqo/ujbuTKrArcqYrFb32xyatFVpdmdFMuQlOQjh/aJv7VNoGC7XzS53cWiEXxpnz6+BZ5jkQiuOj5lCTq72cVWfJcdlYQSptcsBseritizmtNSi6mMAbn/iX0pHa9iuNi3jxqK7x+zF/79vcM936nPrCUsQ7mc0hR/lQ96dpKD1P0E1z6dKzBx39445cB+0tg5cGBXPHb5oThgQMo9SrUE5WIZOnJ4T+zTtxqnNNeCCUs8Ktf6O2hQV/z+7IM82Wp1ikqXjuVxPP9/R+CVq46SBEJxHyB2u56dKtJWslQbIpKQ447XWDTiKS2gjRmKyArT7c0p/bPdp6Xa5P1tPBrBXy8cg+qKeDq+0WRBLheeaa/qCvz89AOwT19vdkIdap1DF5uYMD9Fxd8vGYeKeAzfP2ZvHDCgC6ory3DqqP5W3gwqfmtYW4WWoRZArFsRBt1EInbeeddPDDR1d5YEEGXTFnYjbREz5LfXFy1D4mEey5DwpXjNlGXIu3k3aZFNtLb+PMwk67c499NktglrdVInbdFnW80FIWo1B3Wvwqotu6Xf/viE4dizWRjP1z3aUh6LYkDXKtx19sH4cPV2LNtYazxWdzl1LAzopghDYeoMqQKm8Iyrml3kItLxZsvQIXt0w+ebd0mf+WnVxEU0bF8AUsqSt675Ul7eiRgELhVNVYQhVchWx2ynijhqhYKS4iYpJzla+K1/am3/AHsdJsuQe29BMR0T9+uDuddPTLuqiQK1WrRXPddDF4/Fmm11Umpn1U3ukD264c2fHove1fIcIm7exfPuavDGUUQjmbm5Q3kcPzlpH+P9iLSIZSgHgmKGcuHlHx6FT9fvwDf/MguA/Ex/dvI+6NahHFf/68NUO6JR/O1b5oyXLjYxQyL79euMcUO646G3VwBQU97H8L8rjsz6naTuR7ZGn37QAG9pCJ82Jh0H+/dvFvSi69Kfi8k81PciztfRSERyuxLnF9USpBM+3Hfizr3bm+NEs60HmTqn7rMojt+vDz646YT0OzDHFpqvHfSuOlVm5svD9+qBtz/bnM7MG4RpWpqwdw8cPTzYImYLEygQAPmNGRLpaOEjK2qc1AHX06IwpcgxzYND1ESok4+fe4Yo9IjHqb6+psKRqZihDDrLkM3mpbXXZskwZDjmR82aYZOL3FcO7Iefftm7+YiFtAaoj2cvoXCfbr668LA9AaQyx6iY3I6CHm9ehKG4/fX0bnL+lqFw2eTMlg93wbVxk+tdXaENNPXzt5bdE1tmnrGlSwexFk7mc082uQALtZpNTrQo52voikqBSyYMkb4rkyxDlsKQQePr3rqfld+ds3p2qkiPKVGJFeQmd8yI3jhXcanRzcMDu3XwbPiG96nG5GP3xo1f2U/63HWTEwVX8R5tA/aBtpdNThwn+bZadetYjvFCNtGoMkeK3gO2Ls6qAivIYn/o0B7Suu9JaJHLC3Hkdx8xCPt+bsbidGaqOaQizteRiKwgEucXtdt/7ZABGDeku/RZOoFC2jLU4DlPWLRrjPsMRGHU5Cbn0xeC3tY3x2bG/j59O+P9G4/HfeePDviV/9nDpNS2wc/Vu61Cy1ALkM86Q+InNgv14Xv1TP8tDriD9+iK4X30bl0mvnP0XujbpRKH790TE25/VXuMX5cXN35De3bEWaMHomd1hWdjKm7Qxc2hGjPk3k5Yf/rWrnshLj4mWfEHxw3DeYfuie4dvXFH1RVx3H3uIdrfhY0ZUhdCUQhYsbkW+/aTTfM3n7o/Jh27N3p18grOftpqP/Kx+a4WBOigxV23d1C1rap1MlzMkPxv8Z24i4poG4ppvnfbsLtB1rAC9sJQobPJda0Ss5GJm0Czllc9FkgpR1zXFUB+N9kWxPS0SbDWn7B/H5w1ZmA6JqFccqPynicWjXg0nX5ucuL/9e3yfrZ3r8zcnHQcqR02z8CkUNLx4xNHeD5zEyioGQJd9zm/eVb9qiXm21xOKQoTLa2wFuee8nhUCmYX+7gf6vgJmj9T/SXcmmjDwG5VqTlKsAKlLZ+qq7DrtaEZFiY3+M6GwsKAEucFefyJ+wdVCVBZFsOT3zkMV059D8+8v0a6plvD0N2o52YZ8j5j3WeVBiHDb49oen3lsSheu/oYLF5Xk/ksHtXWrMrm3PmkPVqGKAy1ANkGNusWPbHz+m1+pl15JKZ/sgGXHpHReooa2ZMPCO8zXB6Ppn3PXTzZ5HwWYTdtMZDawP5akzYTSAlwd3z9QAzvU437Zn4mXV9Ep5WysgwFHtFy+D0fnSAEyJpqlVw3GqIgsXTDTgztJcegRaMR9OlcqQ9ENVw6qEn5WJzDWAu0aVeVz1TFQE7Z5JRkEup5ZGFJDKIuwy5BGKquiGNHfROO2Ftf9wuQ+0YuPu/5oHOVfjOjCqtDe8nZjdR3UamkIhctx7n0HPG35YpFTRS4yiUttPeKFfGo9J4A8xh1f+8Xz6XbNIlWttXbdkvtsEqgkOXm4/pT9sWvX1yMX341ZQkW166U4J7awPsZJzyWoaxa0nKI66BtoolskQv9RrOKt4hEUhncTKm2VRzHkebmXBQILvddMBrH7dMb0WjE4zrpXkN0o0zPn5q3L64lYl82zR/i+YDUXNpoiEExdXspVb/rJqeEGNhkfjThZxmSrlEmrw2uIJbN3F1RlnIVXyIksCgPudc0HW1bUsOW9pham8JQC5BNRzetdxHLSW6fvp09AXjighxUoyWIAV2rsHrbbhw9QvYr9VtaNu6stz7/N5qFLlErHo/qIzjECdXmUedjcWhN/Ba/IGvAgxePxbSP1uGJuauMx4wb0h1zlm/BVw7sh337dcZ9F4z2uI3pNoXZWniy/d1+/Tpj4dqUFqw6RByJulCdcVB/T6zdqEFdceyIXnht8UYAGYHGRthU+5Mc/B/1bWO5JAzFpex90354FGYs3oAzDxlovLZUZ6jA2eS6+GxmRM4dvwfWbq/DkcN6Nh8rf18Zl4Wh6soy9OlcgfU19Th6ePhMRjrikvtXFAO7dcAVxw1D56oyY40jl3KdMGTo0+7vw7iVqXyxVY7Vs5m/hvTsiBVK7JkNlx05FN86fLDQb2XLkEsYS1drW+KDEMdJS2usxVt3x+o95x2CGYs3hkpiEI9lhKGgBAoOENiHw1Iej2bqFUpFkGUhI9m8uffLJifKn2I7xflDbbKaAdD03kzKRp0Xg5pgIBfLkG3tJ9EToGNFHNt2NRp/72L6RhePGHavaRqbJsVstjC1NgHg7aCiRqA1kTTSWdQYEPnX9w7D/z5ah7PGKBs15bb6d6nEmuaUxdm48YgFJyORSOCmvKXrRuRKNm/dV6scsAE+dkRvLDakwHW5/1tjMHvZFhzVHBN2omUxy9yCcMNjSroRlORAvNwdZx6Ib4wdpD3u66MHZYShtGYzGPX6WmFIOEZUkokLcKeKONbXZNJ7D+hahfPG75n+930XjMaPnvwAv/vmQcLvM+fNJptcPhELR44b0g0PvLVcW/ujLBbFNUL8m9ofKsrk7HvVlXHMvPpYbN/diD6aJCJ+nDNuDzw+ZyUAeYMlusm57+CHxw+Hin5D433OUm0xQYufrqvmFxNg+OqiwwfjobdX4McnDJc6v834uf3MA3H7/xbhgsP2DDxWxbShEhUIfvNsa8QM5XJK0U2uhQ1D8nWbn+uXR/bDl0eG88woi0ZRh+baTxZuctm6MJuQkxRlPldjIRsVYUj37sV9sXgvYpycX5zTnj06GpPKfOvwwXjlkw3ptSzdNo1lVXUFy8U1LKjOkIs4d1RIVn27dyS66LpulrL7b7h7MI3Nw4aavRGygW5yBIB3cREnDROmoZFLwVBRo5RNwTWRfl2qcIngguci3tX93xqDUYO6Yu6KLbjthUW4zZAcwA9Vo6C7e1G71BYTKOSKn8YqpmhuXV9/AOn4nyBtUXVlGSZaZp8RMffRDDd8ZT/c8txC6ft8eHNJrlNBliHL/iEuSGHc5NRaW3GNtUaUU8R4DnEBrq6Mo0/nSny6fqf2Oifu3xfH39RHuge1vlMhETW7HSvimHPdcVaFENV3UhmPob4p04+rK+OoLIuFnrM6VcQx5WsjM8KQ6LIUFZ9bOH993XgU33lqc+IIfwfUmzF0sutP2Rfnjt8Dw3p3woxmId3veJE+nSsloTkfSCnHLRJCuLSIMJTDScX2hYmtygaxlfmyPATN50lH7iP5eP6yAKQXtFLKGDnWTPeeRNdE8e/OkmXI+7sPbjwBDYkkOlXEjZvrI4f1wlvXfAl9lORQujVAFRxyeT+68aBLbmQqOeA/B8mKFvXe1SQdYTB1jUP3yq8w1B5hNrkWwJNNScqt33ryp6iFqcxh4PtxarPpf0Sfahy3bx/07FSBkw7oh9d/ciwO2aNb6POpA183seu0Pn7kIlDmSjZrr5/GStasZRaTiycMxtPfP7z59/m5328fNRQnj8xYjWwUjpceMQTjlWw+YTPguYguELKbXJBlSK/VVBEXx7jPYq6irstlmo2LbBnKbPTFTXSnijLc9tWRmLhvbzx++aHaa6mLrpRAocAxQ2JbGhNJ9K6utIqR8MQMlUWxuyHjLmiqcq9DPJUqPEmWIaWYswmtm5zmOUvaeklb7tPYZkyuKvFYFMP7VKf6oKKBLwTxaET7dxBtzU1OpKVjhsROZ1Ng2YROwWLCcRxj9spsMb1D09yacZPzWs3PEeroico7KYW+5lpdOpSl6w351a0Z0LXKMxeK/3Qfn8cylEsCBZ3HitZaJAhDWdSI0wk74vsNHTOkaePVJ47w1H4sRWgZagHKfOoMmTYwLVGbQZxEc7UMmZj8pWHYr39njB+SH82C1xzufS7iPGIz8RdybQ6bzhzw7z9ybEUcG3ak4rKG9a5Ov+N8Bda7FdEHX/M8ALN2WO276oYjH66M1aESKIh/m4+Ws4jZPzPVTz0mWR28FiZTLGl1ZRyDunewqj2SOX/bySYHABccuic++GIbJuzdM/jgZtT+UFkWk2JywsyFsUgETc3vw2/zqUtyoUPXx3VpZ02FWsXfP375oTjnr7OsruFHoYQhKSV1iDYUvleayTbRRBgunjAYSzfsxKE5uB6JMWlBqbWTyfy7jpvmTSkxjKaYrfir7x69F354/DBp/NQ3Zca5GMMTJECHjUHRuQ2qwk95LPs9kba4a8AYKReeg98cJH6jz1onnjP3tX7SsXuHOj4SaV1309aCwlALoG5GHUNqSRtymdcky1ALCUPl8ShOyiJTnQlVAxRkGbLZOBViL3H3uQdj7oqtOCWkrzjgL8yY6jSIgu/oPcNb5Gyw3aR6zPp5kM2qw7jJidpLXzc5vWDx1wvHYGttA37y7w+1v1MXAp1lyFRjS0RN722DmhWt0NxyhrceVRCeBAqKMBTqXEJKKz+LkthnKnw2QbpNmbrhmLhvH4wQshGaikCPHNjF3PAQFErmFfuXOOf++bxD8P1/zDf+rkVSa+fpPC0tC0UA3HTq/jmfx8YydNjQHnhn2WacPW4QPvxie/rzfCQMMp3CFJukK00Qi3oVCaJlSCqsGjCVJULGXOvWgHxahnTCTJAFT7yef9FV4ZzCM3ruB0cAyNFNLg8DKW4R9tEeKfxqWoR4hCHhb5M219RHc+m7csxQ+3jVHjc5zTFhBcpcNHTZ8pUD++Pm0/bPSqtrKwyJrmNi/MawPtV4ZtIEvH3Nl0Jf2w/Tragfq/NktoH+ogwhptb++WmpzcaVE4dpfyf5i/s8fnFBExey4/frg2+MHWRcOFThRrw/9+9+Xapw06n74Y4zD/RYO48Z0QuRCHDaQf3NjTMgL6htWQdvRt2sVcSj2npLNoibdFMqfkDuS36bIF1/Ef3+zxo9EH/71hjpHiRNruLvny3iL1vCa8AGXUwdAJw8sp+vENyGveRaNZtcLpievcgjl47DnOuOw8F7dMt7Njl1jO7ZowMA4HAhtkTO6urNoqkTikXLkJQ+O2CnE9YypLOUeSxDOQhD1ZVluOPMA43X1FFhUC54yXwnrjXuO8glm1x+4sna8ADPAVqGWgBVayCllgzbkXLoeHIBvZaxDOUbG42DreZrznXHYc22Ohw4sGuOrWpd/GOG9PFnXZVq3gcN6pr3dtm4TgBeV5R8WIZEn+Yxg7tj8a0nGatm27rJBbmclcWiaGjy+rip67Lkwy24OF48YQgA4KZnF0jHP/CtsahvSnpSvdogWaEKnE0uW7wxQzEcsmdX33TwJuRnrwhDwt/iK/NzUVE3NOXxKC45YghmL98CIJUoQsVkiWwLlrtckNzklHfmNwUXSnizwa/uW1uizMICHI9F0bs6lW1RdtXM/frq+335h0djd2NCUrrpBI4gYUi0DMnFcP3fi1/MkA6d66o6P+RSZwgAvjF2EO58+VOsq7HLnivW8vFL5CG7WGeOc9e7XCxD+RBk4tEI7IumtB8oDLUAagcVB7pJm9sS64e46JsqIbc1wiZQ8KN3dWV6sWhP2GYJEy1D3fJcJ0CHraJbfYe5aCq/OWYQ5q/cipMVd0OTIATYJ1AQF0ddzJCp3Wo2OcnCpDlPo0c4jGQlCKWu1f4tQ+L0WBaLIBaN4OujByEWjWJMSBdP8f2qSgTp9UlzsJ9lKPOjq08cgcuOHIKlGzLZ/jpWaN6bcB1ZW94+34/LsD6d8NLC9QC899LaSWnytT62Zja5XIhLc0rwWWPSnJd7K1SBtjwe9QgTkjDkZtEMaIeoXBLLRARZ7ELHDNlYhvKgrIhbWPDSxwrfN1kWJRVv211nTMo3G/LRP9tb3UZbKAy1AOrkJQ7j0DFDObQjlseiq62FJ2ZI8wTEZ6huTIsBP21PQ0JOQeyiWoZaApPGV31HngQKWU6eDhz86usHNmdLsj9HxHJjEGQZMjVb3U/FA7S4tgufDcUgDInvxFXSpAQic7FZE5LLiMdNLvO37V5K3cxVKAVhdZYh8S0Uwz7hye8chrmfb8FlRwzFCx+tQ5eqMs99tdd5N49DUUu+rGJxy1TwLvmoMyQGxtsIVPFAy5D3N1ccNwwvL1yHCw7bU/p90PgMK8PqlBKqkjEfyQe8qcbNiLcg1mjzQxQS3b6Vi2VocM+OoY7X0RYS97QEFIZaAM+EKPqrm7LJGcSefGnEci262lp46gzpLENFOhhd/AqpNQqruejy0cVycs0FdYHct19nfLK2Bl89ZID0uccylK0w1HyasBsMWy1pkF9+eTyKWk0si+oGKBdd9Z4nn9W4pUyKbdgdyQ/xneQ6L4nn8liGhDnV1j1K0nY3n058zh01qcNbQlO6X//OeT+nLeOGdMe45vT4r1x1NCJo265vYWhpN7l8PSVTPKOJfMQMVcQzdetsziGPFY1lSDMu9ujRAe/deEJz7cXMWpbvlOdi29x2qIlT8iEMifGgnQIS4iQd4J7zDsH6mjrs3bvaeJz41HSWTNmybncP//zuYXjo7RW44ZT9rI73o1j3XxSGWgix+KQDB985aiie/2gtLjliCH7yL32WqnwjaqTbjWXIImaovW4CbanwmeBEP2dxo+7nNpYv9u7dSfr3k985FAvX1GDsYLmukDqBZzt5juhrXjD8sPWflzOzedtYVRbDVjR6Pld7qCwMeS/YtSp/LoziZqN96ubl/pCr3744Ffi5jNg+K128WTSEZShf76R3dSVmXn2MVRHblsQ0dlvdTS5P1+vftSov52lpdElZ/DCldw9DRTyWFoZsllhdbaOgmCHxWNkylN/ZTCoU24JucruE+mgdA1yf9+hehS9bZJeVLNoaRZqkALKcP8cO7u5Zp7PFbz1vz2m3KQy1EJceMSQjDDnAtSfvi2u+vI9UWVzC0L9yWQJEjXQ+Bn5rYBMzVKw+qy5dO5g3zwcN6ooLDt0Tg3t2xIdfbGuV9jw7aQJWbtnlScpQXVmG8ZpMfepkGNaH/bkfHIEn567ClROHh21q6npiliKfa4vubbrjTElHPNnkAlzX/u+4vbFicy2+pljQsqFHx3IcNrQHko6DHq0QJ9YSiI86VyVN0sfqLl7HdoHW9R1R+dJJEzMkCah53Ajs2SN3l5aiIccp/++XjMPrn26UCoDmk4n79sErn6zHZUcOzcv5xJpZNjGkkiUky2dVIdXOCmmNT9cZsm+HOOfmO8uf7CaX+n9LuMnZ1Ed7/PJD8fR7X+DqE/YJfX69ZchsDW8N/JTRE/bqiTeXbkLfzu0vVpvCUCvgdudIJGI0a7bE9l60srQXN4c9undIZ2cBWl8DWUimfG0knpr/Bf7vOHMRtEgkkk5re9nf322Vdo0a1BWjQmSnUxe2sD7GBwzoggMGZF+jJarRCuoQF0ed+4xJGPLEDAUsTl07lOOBi+wLq/oRiUTw2OXj03+3R/KZ5VJ8b37Z5E48oC9+8dxC7BNgbZT7TvP/hfZ20LjJSSm82629rrg5engvHD28V4ud/74LRmPNtt0Y1L1DXs4n15AL3vBKlpAspSFxLNpkpBPX5kydocz3YQSq/LvJedsRj0UhlCXLizBUr8k2qnLYXj1w2F725T1k917v97nEDOUDP2X0XWcfhAffWo5vjmkZpUNLQmGoBRk1sAs++GK7lAnL6HZgsgzlsOFJhExH2Ra485ujcNsLn+DSI5o1bO1zv5cV54zbI5TmUkxT2pbIV8xQtmSTWlunmLS1WsRD+vfnSnsVglykBAq5CkPC356NgXCdAV2r8N4Nxwf69UvxZu4GL8BNTuxv7dVFJCy2XbA9u82EIRaN5E0QAuS6cTbKpHJh3sk2m1xeLEPC78KcIt9bFZNwWC7EReVDGGoJgp6bXGeo9dcCv/7Ys1MFrj4xvAWsLdA2e0OR8MBFYzHlayMx5Wsj05+1ZgaofAZutxYDu3XAn88bjdHNKXbb97avZbn25H3QsTyGn57UtiYfVcvX2pt329TasjDkHSum9NfqsTY1QUgGWRjK7Xn5FVNVX323juWB70fsqm6/FRf/oBie9lLHJlf6dmldN5hSWwdky1Dw3YsWy2yVT2IdnLCniGksQ2EIsgzdd8FodCyP4S8XjA7VHsBc+8svNlektb3ywwlDBXCTK9IwBVqGWpAenSo8mn5j4UpTNrkcrn/siN74+X8XYkA7CRrV0d614C3J/v274IObTrByo2hNWrrKexBSEK/PxC2laNc0ucoyZqjQi1N7Q0rJm2OFSF83uSymDl3shThnd9AIyGJ/aIf6p6w4Zngv/Oj44YFZ7yLIb6KPffpWY9G6HThmRMu5vLUFZMtQ8BgRLZbZW4YEN7ksM3hmu14HCUMn7t8XH958ovVGXIoZErNXxqPY0fy3rWWore1BskmgkE9s+mN7hMJQKxNWqM5lHA7u2RGzrj3OOqd9W6RtTUNtj7YmCAF2/t/DenfCkg07MTKH2CAT8obWrgfpWmxK+3z6QXIihDKpJgh7bBADumWUM3OWb87pXOJ786bWDo+ULri574hxQDo3OVEAKpWYoUgkgh8cNyz0707cv09O1334knF45v3VOGv0oJzO09YRhSGbOUUsBpy1ZSgHN7lo2k0uq0tb1X8Kc19iO0wxndbCkMUxhTKWFKLmT7EmsGp7O6kixyRVt5TyoW+Xypz98gvJtw4fDABmTWBp7D3aFaJlqJtBEP/7JeMw+di98bdvjcn79W3d5ER07k06y9BzPzjCk6JUrhbPKTWIslgUBw5MCcFqhkJb3Fe8b7+MZSIfmZV0qYHF8wZZhkrESy4rTtivD35/9sFZ/dZ9L707V+LbR+2Fbu00k6ItXUImUBDrX2W7V5USKGS5IRF/F8aikm8Lh8lNTryOvWUo+BhdYpVsCUoaJc43hXBZY9FVkhfC7pVKKZuajtF7dsO7101E9yJf/IoJURh659rjtMf071qFH584okWuL87Vtguyzpqli2cZoqngLdUZaqNBuW2NRy8bj7++vgxfO2RgVr//3xVH4uF3Psf/fWkYDp0yHQDQvZM8R2Tj3iJlH2z+s2uHcvzum6NQEY9pFUtif6csJBMRMigcMaxn1oq5UlsHJcuQxeZTjGWzEchPHtkXL3y0Dt87Zi/cM+MzALIFJFvlbNQ7fHy5+sQRePuzTTh1VHD9nTDoCsICshuzrfLEpu/lVeEccDnxXRdC0V2sliEKQ62MOWbIQHH2u1D0qq4odBNICMTFuNCTta3mTBfrobMM6c4nam6LvSBwvuhcWYYfnZC9MLxP38647aupxDS3nL4/3liyCV8fLQtW2bwJ0/z81YPNQpvY32kZ8vLdo/fCjMUbcGaWgm8pUi1kPbSyDAkb5LqmhM+RKe765sH43tE7sF//zmlhqFYoIJrthlcUHGymwknH7o1Jx5pLSWSL7B0gWO6FZ6lzedVhZxnK3zoXdLmOFXE8+Z3DEItGCrK+FqsnOIWhVqZYM3EQ4qIrFNeaZOMmp7cM2QpD4a9H8scFhw3GBYcN9nyejVyazSZQdpOjNKRyzZf3wTVfblsZL9s6ovbfZs8gunztbggOwCmPRzFyoByvKaa3zlapozGsFgSpXpjw/Gp2N6b/7tnJTsnq9yhOG9Uf//lgDX7wpfwLdH6MG9I9+KAWolhdwYvzrtowQ3t2xPA+nTyft7WMJYRkS6GzyWVV+E/T5H5dvFkYdZsE0U2Ow7jtkI1rVTbCLN3kWp5+XdtfRftc6CG4fFaEdL2tawy2DIlMOnYvHDiwC049qH/6s2yVOm1l/hONaeKcvaW2QTjGrrF+88id3xiF6T862mOVzoW2vhf85thU8pJs4z3bKrQMtTLxWBTTrjgKQ3/2gtXx7Tn5ASlN8l1NPCzZFP7TtfmsMQPx7ootWLxuBxaurQGgtxwUq6as3ZNjam1bZDc5ikMiuW7rHr5kHJ6YuwrXn7JfXtrTXuhQHse/v3c4HMcJvQfYHVIYuvrEfXD1icAz761Of5bthjzbBAr5RvIOEKbnsM8G8F9D4rEo9urlVW7ngni5E/brg5cWrsfXDh5gPL61+dohAzCsTycM611d6KbkFa7iBUC3oTKNt5+ftj8Gda/CLWcc0LKNaqdw69H2KLRlKGZwkdBxwn6pVL/njt/T811ZLIrfffMgnDPOP42vZBlikF+bIeeYIctunGA2uRbjqOG98KdzDynJBDqj9+yGMYPDu0Ptbgi/4QfkfYmNTkAnJESzUES1BCY3uWwo5Ix+5zcPwj3nHYJfNsdHtgUikQgOHNjVWJS8vULLUBtnSM+OeOMnXyp0MwixptCFJ0VNYJCb3H0XjEZtQ0Ly0VcJCmCOhk2hRNos2aQULsWiq6Ttko31A5CVSDbjQCf4t5XpT1cvTCRMeuhCWrg6VcTx5ZH5zbRH9NAy1FZoK7MIITnSr0th/fvDJFCIRCK+ghBQvHUVip1s9jC5uskV2kW0rdHGwx+KkrAxQy5ZxVoqtJX3LVm5hL87N2fpM9Yt1NDat9RWnmGpQWGItGtK0X2irfPARWNx2NAe+Pf3DivI9SMhNZxBhCkIyHWs7ZBrAgUnCyfcg/foKv37hxOHhz4HIbmQrTAUMcTZmI/3P0dhs8ll/hYtQ//63uG49IghuOPro6zP1drCCdeQwkBhqI3AARCOP5xzME4b1R8XHT640E0hCvv264zHv30oRu9ZmPSfYd09gti/f5fgg5pp65mASolsXkW272/6j47Gnd8YhdNG9Zc+v2LiMHxw4wlZnZOQMNxy+v7oUB7Dr8+y3+iL5MMyJFHAudAUNzq8TzVu+Mp+oZSorT2nHziwa6tej6RgzBBpl5w2qr9n40EIkP9Ffe/enfDkdw6zKv5LUajt0Jp7mL16dTJmlerSoaz1GtKOOW/8HvjH7JX4xhgWZ82GCw4bjHPG7WFVpFWHqVBpthTUMmRwk8uG1pbpLjgslczn8L17tO6FSxwKQ20EapQJyQ/ZpNYOIqjIXZ/OFVhfU48Je/fMzwVJzjCzX+EJ8w5uOnV/nDaqPw7eo1sLtqi4yVYQAmQLSnvfjkiWoRxvprUfRVksikuOGNKi1+jaoQzbdjUyHlaAbnKEkKJCyiTUSpP9zKuPxdzrJ6JvgZNHkAwtvaEb1D1VlHfffp1b9kIlQnk8ivFDe4SK0SN5JM8W9YKm1o7q/w7D9afsCwD47Teycztsyzx22aE4clhPPPX9wwvdlDYDLUNthPauiSGkrZB333cLKstiLJBcYjx22aF48K0VuPTIltXiEtIahMnCaUMhLbORPFiGLjtyKM4/dM+inNf3698Zj1w6vtDNaFNQGGojUBYiJD/ke1En7ZNcXY+DsmQP6t4BN566X07XKHo4/toNUga29j5xCmM3nq1pCChKQYjooT26jcCYIULygziUOK4IISSYmBRr2b7d5ERykIVICcFuQggpKiKGtKqkNDhun94AgEtbOAiZBMPR137It+Korbx7rgHEBrrJtRE4XAnJP1wHS4+/XDgGG3fU55zMInzJVULaL8U6V7ZW3Chp39AyVCCuO3lfVFdSFiWkJaGbXOkRi0aY1Y+QkORaj0elkFOvI6gyaBkiNlAYKhCXHzVUqkzOPRsh+YcLIcmW8hxqthDS3jhoUFfs07cax+/XJy/nayt1vnKtM0RKg1Cz/ZQpUzB27FhUV1ejd+/eOOOMM7B48WLf3xxzzDGIRCKe/0455ZT0MY7j4MYbb0S/fv1QVVWFiRMnYsmSJdndUTsi35oYQogMhxgJy5UTh+HQod3xlVH9Ct0UQlqNslgU/7viSPz1wjGFbkpe4T6L2BBKGJo5cyYmTZqEWbNm4eWXX0ZjYyNOOOEE1NbWGn/z1FNPYe3aten/FixYgFgshrPOOit9zB133IE//OEPuPfeezF79mx07NgRJ554Iurq6rK/s3YHBywh+Yb+4iQsV04cjqnfPgwVcabVzRUOv/ZFGLfir48eCAA4cGAXw8ny0aLsCEqLT4hKqKCVadOmSf9+6KGH0Lt3b8ybNw9HHXWU9jfdu3eX/j116lR06NAhLQw5joO77roL119/PU4//XQAwMMPP4w+ffrgmWeewdlnnx2miYQQkoabMUIIyT8XTxiC/fp1xkiDMMSpl7QncnKK3r59OwCvwOPH/fffj7PPPhsdO3YEACxfvhzr1q3DxIkT08d06dIF48ePxzvvvKM9R319PWpqaqT/2jvctBGSf+gvTkjhaCtxIyT/xKIRHL53T1RXlmm/79qhvJVbREj2ZC0MJZNJXHnllZgwYQIOOOAAq9/MmTMHCxYswGWXXZb+bN26dQCAPn3koL0+ffqkv1OZMmUKunTpkv5v0KBBWd5F24FLBiH5h25yhBDSetxx5oE4/9A90vW+CgHd5EhYshaGJk2ahAULFmDq1KnWv7n//vsxcuRIjBs3LtvLAgCuvfZabN++Pf3fqlWrcjofIaQ4oSxECCGtxzfGDsKtZ4wsaOKCjhUsW0LCkVWPmTx5Mp577jm8/vrrGDhwoNVvamtrMXXqVPziF7+QPu/bty8AYP369ejXL5O9Z/369TjooIO056qoqEBFRUU2TW9z7NO3GovW7cApBzJzESH5hnWGCCkcHH6kEBw6tDvOHjsIe/fuVOimkHZCKGHIcRz84Ac/wNNPP40ZM2ZgyJAh1r/95z//ifr6epx//vnS50OGDEHfvn0xffr0tPBTU1OD2bNn43vf+16Y5rVLHrv8ULyxZCNO3L9voZtCCCGEENKuiUQiuP3MAwvdDNKOCCUMTZo0CY899hieffZZVFdXp2N6unTpgqqqKgDAhRdeiAEDBmDKlCnSb++//36cccYZ6NGjh/R5JBLBlVdeiVtvvRXDhg3DkCFDcMMNN6B///4444wzcri19kH3juU4/aABhW4GIYQQQgghJUcoYeiee+4BkCqkKvLggw/ioosuAgCsXLkS0agcirR48WK8+eabeOmll7Tn/clPfoLa2lp8+9vfxrZt23DEEUdg2rRpqKysDNM8QgghhBBCCLEmtJtcEDNmzPB8NmLECN/fRiIR/OIXv/DEExFCCCGkfcKQIUJIeyCnOkOEENLWGNGnutBNIIQQQkg7gfkHCSFFRd8ulXjxyqPQuYrTGyGEEEL8oWWIEFJ0jOhbjX5dqgrdDEIAAJdMSGVe/dZhexa4Ja0LU9sTQtoDVJ0SQgghLch1p+yLrx48APv171zophBCCFGgMEQIIYS0ILFoBCMHdil0M1od2oUIIe0BuskRQgghhBBCShIKQ4QQQgghhJCShMIQIYQQQgghpCShMEQIIYQQQggpSSgMEUIIIST/MIMCIaQdQGGIEEIIIYQQUpJQGCKEEEJI3qFhiBDSHqAwRAghhBBCCClJKAwRQgghhBBCShIKQ4QQQgghhJCShMIQIYQQQgghpCShMEQIIYSQvBOJMIUCIaTtQ2GIEEIIIYQQUpJQGCKEEEJI3unftarQTSCEkEAoDBFCCCEkbzz5ncNw9PBe+PN5hxS6KYQQEki80A0ghBBCSPEwbkh3jBsyrtDNIIQQK2gZIoQQQgghhJQkFIYIIYQQQgghJQmFIUIIIYQQQkhJQmGIEEIIIYQQUpJQGCKEEEIIIYSUJBSGCCGEEEIIISUJhSFCCCGEEEJISUJhiBBCCCGEEFKSUBgihBBCCCGElCQUhgghhBBCCCElCYUhQgghhBBCSElCYYgQQgghhBBSklAYIoQQQgghhJQkFIYIIYQQQgghJUm80A3IB47jAABqamoK3BJCCCGEEEJIIXFlAldG8KMohKEdO3YAAAYNGlTglhBCCCGEEELaAjt27ECXLl18j4k4NiJTGyeZTGLNmjWorq5GJBIpdHNQU1ODQYMGYdWqVejcuXOhm0PaIOwjxAb2E2ID+wmxgf2EBFFMfcRxHOzYsQP9+/dHNOofFVQUlqFoNIqBAwcWuhkeOnfu3O47E2lZ2EeIDewnxAb2E2ID+wkJolj6SJBFyIUJFAghhBBCCCElCYUhQgghhBBCSElCYagFqKiowE033YSKiopCN4W0UdhHiA3sJ8QG9hNiA/sJCaJU+0hRJFAghBBCCCGEkLDQMkQIIYQQQggpSSgMEUIIIYQQQkoSCkOEEEIIIYSQkoTCECGEEEIIIaQkoTBECCGEEEIIKUkoDOWZP/3pTxg8eDAqKysxfvx4zJkzp9BNIq3ElClTMHbsWFRXV6N3794444wzsHjxYumYuro6TJo0CT169ECnTp1w5plnYv369dIxK1euxCmnnIIOHTqgd+/euPrqq9HU1NSat0Jakdtvvx2RSARXXnll+jP2EwIAq1evxvnnn48ePXqgqqoKI0eOxNy5c9PfO46DG2+8Ef369UNVVRUmTpyIJUuWSOfYsmULzjvvPHTu3Bldu3bFpZdeip07d7b2rZAWIJFI4IYbbsCQIUNQVVWFvfbaC7fccgvEJMHsI6XH66+/jlNPPRX9+/dHJBLBM888I32frz7x4Ycf4sgjj0RlZSUGDRqEO+64o6VvreVwSN6YOnWqU15e7jzwwAPOxx9/7Fx++eVO165dnfXr1xe6aaQVOPHEE50HH3zQWbBggfP+++87J598srPHHns4O3fuTB/z3e9+1xk0aJAzffp0Z+7cuc6hhx7qHH744envm5qanAMOOMCZOHGi89577zkvvPCC07NnT+faa68txC2RFmbOnDnO4MGDnQMPPNC54oor0p+zn5AtW7Y4e+65p3PRRRc5s2fPdpYtW+a8+OKLztKlS9PH3H777U6XLl2cZ555xvnggw+c0047zRkyZIize/fu9DEnnXSSM2rUKGfWrFnOG2+84ey9997OOeecU4hbInnml7/8pdOjRw/nueeec5YvX+7885//dDp16uT8/ve/Tx/DPlJ6vPDCC851113nPPXUUw4A5+mnn5a+z0ef2L59u9OnTx/nvPPOcxYsWOA8/vjjTlVVlXPfffe11m3mFQpDeWTcuHHOpEmT0v9OJBJO//79nSlTphSwVaRQbNiwwQHgzJw503Ecx9m2bZtTVlbm/POf/0wf88knnzgAnHfeecdxnNQkFo1GnXXr1qWPueeee5zOnTs79fX1rXsDpEXZsWOHM2zYMOfll192jj766LQwxH5CHMdxfvrTnzpHHHGE8ftkMun07dvX+fWvf53+bNu2bU5FRYXz+OOPO47jOAsXLnQAOO+++276mP/9739OJBJxVq9e3XKNJ63CKaec4lxyySXSZ1/72tec8847z3Ec9hHieIShfPWJP//5z063bt2k9eanP/2pM2LEiBa+o5aBbnJ5oqGhAfPmzcPEiRPTn0WjUUycOBHvvPNOAVtGCsX27dv/v737C2mqD+MA/n3dabMROmV5VsbCIFqlF8uRLKMbI5EuoougEBndRKWkFYUUXVpedVEXRV3URcbooujPRTA2KwY2bG3mimbQH7twSX/GBIOW53kvwvN63skLL8yt3PcDAzm/h/H7sS/uPGw+AgCqq6sBANFoFNls1pARl8sFp9OpZ2RoaAgNDQ1QVVWvaW1tRSaTwcuXLwu4e1ponZ2d2LlzpyEPAHNCv9y7dw8ejwd79uxBTU0N3G43rl69qq+/e/cOqVTKkJPKyko0NTUZcmKz2eDxePSa7du3o6ysDJFIpHCHoQWxZcsWBINBjI2NAQBGRkYQDofR1tYGgBmhXPnKxNDQELZt2waz2azXtLa2IplM4tu3bwU6Tf4oxd7AYvH582fMzMwYbk4AQFVVvH79uki7omLRNA09PT1obm5GfX09ACCVSsFsNsNmsxlqVVVFKpXSa+bL0OwaLQ5+vx/Pnz/H8PBwzhpzQgDw9u1bXLp0CceOHcOpU6cwPDyMI0eOwGw2w+fz6a/zfDmYm5OamhrDuqIoqK6uZk4Wgd7eXmQyGbhcLphMJszMzKCvrw/t7e0AwIxQjnxlIpVKoa6uLuc5ZteqqqoWZP8Lhc0Q0QLo7OxEIpFAOBwu9lboN/Px40d0d3cjEAigvLy82Nuh35SmafB4PDh79iwAwO12I5FI4PLly/D5fEXeHf0Obt26hYGBAdy8eRMbN25EPB5HT08PVq5cyYwQ/Q/8mlye2O12mEymnIlPnz59gsPhKNKuqBi6urrw4MEDDA4OYtWqVfp1h8OBHz9+IJ1OG+rnZsThcMybodk1+vNFo1FMTk5i06ZNUBQFiqLg8ePHuHDhAhRFgaqqzAlhxYoV2LBhg+Ha+vXrMT4+DuCf1/m/3nMcDgcmJycN6z9//sTXr1+Zk0XgxIkT6O3txd69e9HQ0ICOjg4cPXoU586dA8CMUK58ZWKxvQexGcoTs9mMxsZGBINB/ZqmaQgGg/B6vUXcGRWKiKCrqwt37txBKBTK+Qi5sbERS5YsMWQkmUxifHxcz4jX68Xo6KjhF1EgEEBFRUXOjRH9mVpaWjA6Oop4PK4/PB4P2tvb9Z+ZE2pubs4ZzT82NobVq1cDAOrq6uBwOAw5yWQyiEQihpyk02lEo1G9JhQKQdM0NDU1FeAUtJCmp6dRVma8jTOZTNA0DQAzQrnylQmv14snT54gm83qNYFAAOvWrfvjviIHgKO188nv94vFYpHr16/Lq1ev5MCBA2Kz2QwTn2jxOnTokFRWVsqjR49kYmJCf0xPT+s1Bw8eFKfTKaFQSJ49eyZer1e8Xq++PjsyeceOHRKPx+Xhw4eyfPlyjkxe5OZOkxNhTujX2HVFUaSvr0/evHkjAwMDYrVa5caNG3pNf3+/2Gw2uXv3rrx48UJ27do174hct9stkUhEwuGwrF27lmOTFwmfzye1tbX6aO3bt2+L3W6XkydP6jXMSOmZmpqSWCwmsVhMAMj58+clFovJhw8fRCQ/mUin06KqqnR0dEgikRC/3y9Wq5WjtemXixcvitPpFLPZLJs3b5anT58We0tUIADmfVy7dk2v+f79uxw+fFiqqqrEarXK7t27ZWJiwvA879+/l7a2Nlm6dKnY7XY5fvy4ZLPZAp+GCunfzRBzQiIi9+/fl/r6erFYLOJyueTKlSuGdU3T5MyZM6KqqlgsFmlpaZFkMmmo+fLli+zbt0+WLVsmFRUVsn//fpmamirkMWiBZDIZ6e7uFqfTKeXl5bJmzRo5ffq0YdwxM1J6BgcH570X8fl8IpK/TIyMjMjWrVvFYrFIbW2t9Pf3F+qIefeXyJx/VUxERERERFQi+DdDRERERERUktgMERERERFRSWIzREREREREJYnNEBERERERlSQ2Q0REREREVJLYDBERERERUUliM0RERERERCWJzRAREREREZUkNkNERERERFSS2AwREREREVFJYjNEREREREQl6W8PxCCzwYUGKQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "psize = get_period_size(400.0)\n",
    "apply_chirp(fullfreq,fullfreq.shape[0])\n",
    "tfull = np.fft.ifft(fullfreq)\n",
    "idata = integral_data(tfull,tfull.shape[0])\n",
    "plt.figure(figsize=(10,5))\n",
    "plt.plot(idata)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.10.8 64-bit",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.8"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "b0fa6594d8f4cbf19f97940f81e996739fb7646882a419484c72d19e05852a7e"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
